Bind the rows of sheets in a 3d array to make a 2d array

Question

I have a 3-dimensional array and would like to collapse to a 2-dimensional by stacking one dimension by rows (combining rows of one dimension). In my code, I have filled a "worksheet" (3rd dimension) with a 2-d array at each index, and now I want to take that 3-d array and stack these sheets' rows on top of one another.

Here an example array so I can explain what I want the end result to look like:

x <- array(1:24, dim=c(2, 3, 4),
           dimnames=list(letters[1:2], LETTERS[1:3], letters[23:26]))
dim(x)

I would like w, x, y, z to be stacked on top of one another in a 2-dimensional array, which would have 8 rows and 3 columns. Here is a way to do it that is cumbersome (and not possible in my loop):

x1<-x[,,1]
x2<-x[,,2]
x3<-x[,,3]
x4<-x[,,4]

All<-rbind(x1,x2,x3,x4)

I have looked at abind and adrop but they are not quite right.

I have also tried aperm but I don't think you can reduce dimensions with this, just transpose (?)

Alternatively, I could create a list (this would be ideal, actually, since arrays might have different row numbers). In that case, how would I combine the rows of multiple elements in a list the same way?

Answer 1

I'll promote my comment to an answer, though I still think there should be a way to do this just altering the dimensions.

apply(x, 2, c)
#or if you're really pushing for speed, the simpler function:
apply(x, 2, identity)

# Giving:
#      A  B  C
#[1,]  1  3  5
#[2,]  2  4  6
#[3,]  7  9 11
#[4,]  8 10 12
#[5,] 13 15 17
#[6,] 14 16 18
#[7,] 19 21 23
#[8,] 20 22 24

Matches the requested output sans the rownames:

all.equal(apply(x,2,c), All, check.attributes=FALSE)
#[1] TRUE

Answer 2

Here's how to do it by manipulating the dimensions:

y <- aperm(x, c(1, 3, 2))
dim(y) <- c(prod(dim(x)[-2]), dim(x)[2])
# the above evaluates to c(8, 3)

y

#      [,1] [,2] [,3]
# [1,]    1    3    5
# [2,]    2    4    6
# [3,]    7    9   11
# [4,]    8   10   12
# [5,]   13   15   17
# [6,]   14   16   18
# [7,]   19   21   23
# [8,]   20   22   24    

Follow up with colnames(y) <- colnames(x) if you need to.