Question

I have an array in R, created by a function like this:

A <- array(data=NA, dim=c(2,4,4), dimnames=list(c("x","y"),NULL,NULL))

And I would like to select along one dimension, so for the example above I would have:

A["x",,]
dim(A["x",,])    #[1] 4 4

Is there a way to generalize if I do not know in advance how many dimensions (in addition to the named one I want to select by) my array might have? I would like to write a function that takes input that might formatted as A above, or as:

B <- c(1,2)
names(B) <- c("x", "y")

C <- matrix(1, 2, 2, dimnames=list(c("x","y"),NULL))

Background

The general background is that I am working on an ODE model, so for deSolve’s ODE function it must take a single named vector with my current state. For some other functions, like calculating phase-planes/direction fields, it would be more practical to have a higher-dimensional array to apply the differential equation to, and I would like to avoid having many copies of the same function, simply with different numbers of commas after the dimension I want to select.

Answer 1

I spent quite a lot of time figuring out the fastest way to do this for plyr, and the best I could come up with was manually constructing the call to [:

index_array <- function(x, dim, value, drop = FALSE) { 
  # Create list representing arguments supplied to [
  # bquote() creates an object corresponding to a missing argument
  indices <- rep(list(bquote()), length(dim(x)))
  indices[[dim]] <- value

  # Generate the call to [
  call <- as.call(c(
    list(as.name("["), quote(x)),
    indices,
    list(drop = drop)))
  # Print it, just to make it easier to see what's going on
  print(call)

  # Finally, evaluate it
  eval(call)
}

(You can find more information about this technique at https://github.com/hadley/devtools/wiki/Computing-on-the-language)

You can then use it as follows:

A <- array(data=NA, dim=c(2,4,4), dimnames=list(c("x","y"),NULL,NULL))
index_array(A, 2, 2)
index_array(A, 2, 2, drop = TRUE)
index_array(A, 3, 2, drop = TRUE)

It would also generalise in a straightforward way if you want to extract based on more than one dimension, but you’d need to rethink the arguments to the function.