if-else vs ifelse with lists

Question

Why do the if-else construct and the function ifelse() behave differently?

mylist <- list(list(a=1, b=2), list(x=10, y=20))

l1 <- ifelse(sum(sapply(mylist, class) != "list")==0, mylist, list(mylist))

l2 <-
if(sum(sapply(mylist, class) != "list") == 0){  # T: all list elements are lists
  mylist
} else {
  list(mylist)
}

all.equal(l1,l2)
#  [1] "Length mismatch: comparison on first 1 components"

Answer 1

From the ifelse documentation:

 ‘ifelse’ returns a value with the same shape as ‘test’ which is
 filled with elements selected from either ‘yes’ or ‘no’ depending
 on whether the element of ‘test’ is ‘TRUE’ or ‘FALSE’.

So your input has length one so the output is truncated to length 1.

You can also see this illustrated with a more simple example:

ifelse(TRUE, c(1, 3), 7)
# [1] 1

Answer 2

if ( cond) { yes } else { no } is a control structure. It was designed to effect programming forks rather than to process a sequence. I think many people come from SPSS or SAS whose authors chose "IF" to implement conditional assignment within their DATA or TRANSFORM functions and so they expect R to behave the same. SA and SPSS both have implicit FOR-loops in there Data steps. Whereas R came from a programming tradition. R's implicit for-loops are built in to the many vectorized functions (including ifelse). The lapply/sapply fucntions are the more Rsavvy way to implement most sequential processing, although they don't succeed at doing lagged variable access, especially if there are any randomizing features whose "effects" get cumulatively handled.

ifelse takes an expression that builds a vector of logical values as its first argument. The second and third arguments need to be vectors of equal length and either the first of them or the second gets chosen. This is similar to the SPSS/SAS IF commands which have an implicit by-row mode of operation.