R, rmarkdown, cache and objects

If your rmarkdown takes hours to generate, and you want to be able to generate different document output types on the fly, using the output_format option from rmarkdown::render is extremely annoying: every time you change the output format, the cache is reset, so you need to wait hours to get the other format.

I found no clean solution to this problem, but here is an ugly hack. We create a copy of the document and render it. First time it will take hours, but then the cache will be separate from your original document:

file.copy("test.rmd", "test_html.rmd", overwrite=TRUE)
rmarkdown::render("test_html.rmd")

Of course, this is annoying, and we can wrap this two commands with a function. But beware! Markdown by default evaluates in its parent environment, so to make sure it is evaluated in the global environment, you need to set an option. Here is a wrapper function which also opens by default the resulting document in google-chrome:

myrender <- function(fn, open=TRUE) {

  fb <- gsub("\\.rmd$", "", fn, ignore.case=TRUE)
  fn2 <- paste0(fb, "_html.rmd")
  file.copy(fn, fn2, overwrite=T)
  res <- render(fn2, output_format="html_document", envir=globalenv())
  system(sprintf("google-chrome %s", res))
  res
} 

Accessing object from another package by variable

Say the package name is stored in variable x and the name of the object you would like to access from that package (without loading the package) is stored in y. Of course the :: will not work, but fortunately it is just a wrapper around the function getExportedValue, so the following will work:

getExportedValue(x, y)

Add a file to scan when completing in vim

OK, so this was an easy thing to find out, but enormously useful.

In vim, Ctrl-P and Ctrl-N allow to complete a word in insert mode. By default (see the complete option) vim scans the current buffer, buffers in other windows, included files etc. However, to add a specific file (in my case, bibliography which I like to have opened in another terminal) you need to add a k to the complete option, plus the location of the file:

:set complete+=k./bibliography.bib

Using caret

A caret call I frequently use. Given that x is training data and y response,

library(doMC)
registerDoMC(cores=6)

tc <- trainControl(method="repeatedcv", number=10, repeats=1, 
  returnData=TRUE, savePredictions="all", verboseIter=TRUE, classProbs=TRUE)
mod <- train(x=x, y=y, trControl=tc, method="rf",
  tuneGrid=data.frame(mtry=500))
  • library(doMC) and registerDoMC allow me to use more than one processor
  • repeatedcv: if more than one repeat of k-fold crossvalidation is requested, the repeated= parameter should be modified. repeatedcv must be used instead of cv
  • savePredictions: if we want to evaluate predictions on our own
  • verboseIter: to see the progress
  • classProbs: to report class probabilities, so we can use them to calculate ROC post factum
  • tuneGrid: if not specified, caret will tune parameters. Normally, we don’t want that

R, shiny and source()

This one cost me more time to figure out than it should have. The reason being, it turns out that I never properly understood what the source() function does.

So here is the story: I was setting up a shiny server for a student based on her code. She was running the shiny app from within RDesktop, and so before starting the app with runApp() she would load all necessary object and source() a file called helpers.R with some common calculations.

In order to put the app on a server, I have moved these pre-runApp() initializations into ui.R and server.R. Suddenly, weird errors appeared. The functions in the helpers.R no longer seemed to be able to find anything in the parent environment — object X not found! Even though I called source() immediately after loading the necessary objects into the environment:

# file server.R
load("myobjects.rda")
source("helpers.R")

The solution was, as usual, to read documentation. Specifically, documentation on source():

local   TRUE, FALSE or an environment, determining where the 
        parsed expressions are evaluated. FALSE (the default) 
        corresponds to the user's workspace (the global 
        environment) and TRUE to the environment from which 
        source is called.

The objects which I have load()-ed before were not in the global environment, but instead in another environment created by shiny. However, the expressions from helpers.R were evaluated in the global environment. Thus, a new function defined in helpers.R could be seen from inside server.R, but an object loaded from server.R could not be seen by helpers.R.

It is the first time that I have noticed this. Normally, I would use a file such as helpers.R only to define helper functions, and actually call them from server.R or ui.R. However, I was thinking that source() is something like #include in C, simply calling the commands in the given file as if they were inserted at this position into the code — or called from the environment from which source() was called.

This is not so.

Adding figure labels (A, B, C, …) in the top left corner of the plotting region

I decided to submit a manuscript using only R with knitr, pandoc and make. Actually, it went quite well. Certainly, revisions of manuscript with complex figures did not require much of manual work once the R code for the figures has been created. The manuscript ended up as a Word file (for the sake of co-authors), looking no different than any other manuscript. However, you can look up precisely how all the figures have been generated and, with a single command, re-create the manuscript (with all figures and supplementary data) after you changed a parameter.

One of the small problems I faced was adding labels to pictures. You know — like A, B, C… in the top right corner of each panel of a composite figure. Here is the output I was striving at:

Doing it proved to be more tedious than I thought at first. By default, you can only plot things in the plotting region, everything else gets clipped — you cannot put arbitrary text anywhere outside the rectangle containing the actual plot:

plot(rnorm(100))
text(-20, 0, "one two three four", cex=2)

This is because the plotting are is the red rectangle on the figure below, and everything outside will not be shown by default:

One can use the function mtext to put text on the margins. However, there is no simple way to say “put the text in the top left corner of the figure”, and the results I was able to get were never perfect. Anyway, to push the label really to the very left of the figure region using mtext, you first need to have the user coordinate of that region (to be able to use option ‘at’). However, if you know these coordinates, it is much easier to achieve the desired effect using text.

First, we need to figure out a few things. To avoid clipping of the region, one needs to change the parameter xpd:

par(xpd=NA)

Then, we need to know where to draw the label. We can get the coordinates of the device (in inches), and then we can translate these to user coordinates with appropriate functions:

plot(rnorm(100))
di <- dev.size("in")
x <- grconvertX(c(0, di[1]), from="in", to="user")
y <- grconvertY(c(0, di[2]), from="in", to="user")

x[1] and y[2] are the coordinates of the top left corner of the device… but not of the figure. Since we might have manipulated the layout, for example, by calling par(mfrow=...) or layout to put multiple plots on the device, and we would like to always label the current plot only (i.e. put the label in the corner of the current figure, not of the whole device), we have to take this into account as well:

fig <- par("fig")
x <- x[1] + (x[2] - x[1]) * fig[1:2]
y <- y[1] + (y[2] - y[1]) * fig[3:4]

Before plotting, we have to adjust this position by half of the text string width and height, respectively:

txt <- "A"
x <- x[1] + strwidth(txt, cex=3) / 2
y <- y[2] - strheight(txt, cex=3) / 2
text(x, y, txt, cex=3)

Looks good! That is exactly what I wanted:

Below you will find an R function that draws a label in one of the three regions — figure (default), plot or device. You specify the position of the label using the labels also used by legend: “topleft”, “bottomright” etc.

First, a few examples how to use it:

Basic use:

par(mfrow=c(2,2))
sapply(LETTERS[1:4], function(x) { 
    plot(rnorm(100))
    fig_label(x, cex=2) 
})

Result:

Plotting at different positions and in different regions:

plot(rnorm(100))
for(i in c("topleft", "topright", "top", 
           "left", "center", "right", 
           "bottomleft", "bottom", "bottomright")) {
    fig_label(i, pos=i, cex=2, col="blue")
    fig_label(i, pos=i, cex=1.5, col="red", region="plot")
}

Result:

All the different regions:

par(mfrow=c(2,2))
sapply(LETTERS[1:4], function(x) { 
    plot(rnorm(100))
    fig_label("figure region", cex=2, col="red") 
    fig_label("plot region", region="plot", cex=2, col="blue")
})
fig_label("device region", cex=2, pos="bottomright", 
  col="darkgreen", region="device")

Result:

And here is the function:

fig_label <- function(text, region="figure", pos="topleft", cex=NULL, ...) {

  region <- match.arg(region, c("figure", "plot", "device"))
  pos <- match.arg(pos, c("topleft", "top", "topright", 
                          "left", "center", "right", 
                          "bottomleft", "bottom", "bottomright"))

  if(region %in% c("figure", "device")) {
    ds <- dev.size("in")
    # xy coordinates of device corners in user coordinates
    x <- grconvertX(c(0, ds[1]), from="in", to="user")
    y <- grconvertY(c(0, ds[2]), from="in", to="user")

    # fragment of the device we use to plot
    if(region == "figure") {
      # account for the fragment of the device that 
      # the figure is using
      fig <- par("fig")
      dx <- (x[2] - x[1])
      dy <- (y[2] - y[1])
      x <- x[1] + dx * fig[1:2]
      y <- y[1] + dy * fig[3:4]
    } 
  }

  # much simpler if in plotting region
  if(region == "plot") {
    u <- par("usr")
    x <- u[1:2]
    y <- u[3:4]
  }

  sw <- strwidth(text, cex=cex) * 60/100
  sh <- strheight(text, cex=cex) * 60/100

  x1 <- switch(pos,
    topleft     =x[1] + sw, 
    left        =x[1] + sw,
    bottomleft  =x[1] + sw,
    top         =(x[1] + x[2])/2,
    center      =(x[1] + x[2])/2,
    bottom      =(x[1] + x[2])/2,
    topright    =x[2] - sw,
    right       =x[2] - sw,
    bottomright =x[2] - sw)

  y1 <- switch(pos,
    topleft     =y[2] - sh,
    top         =y[2] - sh,
    topright    =y[2] - sh,
    left        =(y[1] + y[2])/2,
    center      =(y[1] + y[2])/2,
    right       =(y[1] + y[2])/2,
    bottomleft  =y[1] + sh,
    bottom      =y[1] + sh,
    bottomright =y[1] + sh)

  old.par <- par(xpd=NA)
  on.exit(par(old.par))

  text(x1, y1, text, cex=cex, ...)
  return(invisible(c(x,y)))
}