Working with Matrix

Hello Rui/Jorge,

This is shorter, and probably needs less memory for large matrices as
you create
an other copy by defining nas:

matrixOp <- function(m1, m2, op=`+`) {
 rows <- min(nrow(m1), nrow(m2))
 cols <- ncol(m1)
 op(m1[1:rows, 1:cols], m2[1:rows, 1:cols])
}

Best,

mem

On 4 January 2013 14:08, Rui Barradas <ruipbarradas at sapo.pt> wrote:

Hello,

Using part of your code, it's possible to do without Reduce, have foo (fun,
below) do the job.

fun <- function(x, y, FUN = `+`){
    if(nrow(x) < nrow(y)){
        nas <- matrix(NA, ncol = ncol(x), nrow = nrow(y) - nrow(x))
        x <- rbind(x, nas)
    }else{
        nas <- matrix(NA, ncol = ncol(y), nrow = nrow(x) - nrow(y))
        y <- rbind(y, nas)
    }
    FUN(x, y)
}

fun(Mat1, Mat2)
fun(Mat1, Mat2, `*`)  # Note the back quotes


Hope this helps,

Rui Barradas
Em 04-01-2013 12:06, Jorge I Velez escreveu:

Dear Christofer,

You can try the following:

# proccess the matrices
foo <- function(m1, m2){
  if(ncol(m1) != ncol(m2)) stop('number of columns should be equal')
  if(nrow(m1) < nrow(m2)){
nas <- matrix(NA, ncol = ncol(m1), nrow = nrow(m2) - nrow(m1))
  m1 <- rbind(m1, nas)
}
else{
  nas <- matrix(NA, ncol = ncol(m1), nrow = nrow(m1) - nrow(m2))
m2 <- rbind(m2, nas)
  }
  list(m1, m2)
}

# process
r <- foo(Mat1, Mat2)

# basic operations
Reduce("+", r)
Reduce("*", r)
Reduce("/", r)
Reduce("-", r)

HTH,
Jorge.-


On Fri, Jan 4, 2013 at 10:47 PM, Christofer Bogaso <> wrote:

Hello again,

Let say I have 2 matrices which equal number of columns but different
number of rows like:

Mat1 <- matrix(1:20, 4, 5)
Mat2 <- matrix(1:25, 5, 5)

Now for each column 1-to-5 I need to fetch the corresponding columns
of these 2 matrices and add the corresponding elements (ignoring NA
values if any). Therefore for the 1st column I need to do:

(1+1), (2+2),...,(4+4), (NA+5)

and so on

And the resulting numbers will be stored in some other matrix

Also note that, here I gave the example of addition, however, this can
be any user defined function.

Is there any R way to do that, without using any for-loop?

Thanks and regards,

        [[alternative HTML version deleted]]