I wrote already about changing figure options mid-chunk in reproducible research. This can be important  e.g. if you are looping through a dataset to produce a graphic for each variable but the figure width or height need to depend on properties of the variables, e.g. if you are producing histograms and want the figures to be a bit wider when there are more bins.

That previous post was about knitr, but at the moment I am using the pander package more than knitr because it makes some things simpler. Changing figure options is a case in point.

Here is the output:

Varying widths for graphs in a loop using the pander package

Results for: mpg

Anything you type here will be inside the same paragraph as the figure and so works like a pseudocaption

Results for: cyl

Anything you type here will be inside the same paragraph as the figure and so works like a pseudocaption

And here is the code:

Varying widths for graphs in a loop using the pander package ================ <% for (varn in names(mtcars[,1:2))   { %><%= var=mtcars[,varn] pandoc.p.return(“”) pandoc.header.return(paste(“Results for: “,varn,”"),3) pandoc.p.return(“”) fac=(100*log(length(unique(var))))#calculate some factor to ensure somewhat wider graphs for more bins

%><% evals.option(“width”,50+fac) %><%= #have to break out of the BRCODES to change the height options for the next chunk qplot(var,geom=”bar”)+xlab(varn)%> </br>Anything you type here will be inside the same paragraph as the figure and so works like a pseudocaption<% #   coord_flip() %><% } %>

Oh, and to make it all happen:

library(pander)

library(ggplot)

Pandoc.brew(convert=”html”,output=”loop”,”nameOfFileContainingTheAboveScript.R”)