Generalising to n-dimensions

 Hi R-helpers,

I have two queries relating to generalising to n dimensions:

What I want to do in the first one is generalise the following statement:
expand<-expand.grid(1:x[1],1:x[2],...1:x[n]) where x is a vector of integers
and expand.grid gives every combination of the set of numbers, so for
example, expand.grid(1:2, 1:3) takes 1,2 and 1,2,3  and gives 1,1   2,1
1,2   2,2   1,3   2,3
My x vector has varying lengths and I can't find a way of giving it every
set without stating each set individually.

Secondly and similarly, I want to get the table within crosstable that has
the elements defined by the combinations given in expand above
crosstable[,,expand[d,1],expand[d,2],expand[d,3],...expand[d,n]] where
crosstable is just a crosstabulation of an n+2-dimensional dataset and I am
trying to pick out those that are in combination 'd' of expand.
So for example, using x[1]=2 and x[2]=3 as above example, if d =2 then the
order is 2,1 so I take crosstable[,,2,1].

Can anyone suggest a way to give the code every set without stating each set
individually?

Thank you

	[[alternative HTML version deleted]]

crosstable[,,expand[d,1],expand[d,2],expand[d,3],...expand[d,n]]
 
crosstable is just a crosstabulation of an n+2-dimensional dataset and 
I am trying to pick out those that are in combination 'd' of expand. 
So for example, for 5-dimensional data using your example:
 
 Var1 Var2 Var3
1     1    1    1
2     2    1    1
3     3    1    1
4     1    2    1
5     2    2    1
6     3    2    1
7     1    1    2
8     2    1    2
9     3    1    2
10    1    2    2
11    2    2    2
12    3    2    2
 
d refers to the row of the matrix above - d=2 is 2,1,1 so 
crosstable[,,2,1,1] would retrieve all the data where Var1 =2, Var2=1, 
Var3=1 and the two remaining variables are given in the 
crosstabulations for all values.
 
Is that any better?

Sorry to hassle you, but I really need to get my code up and running.  
Please can you therefore explain what a and v are?

Thank you,

Laura

On Wed, Sep 24, 2008 at 8:27 PM, Laura Bonnett 
<l.j.bonnett at googlemail.com <mailto:l.j.bonnett at googlemail.com>> wrote:

    Can I ask what a and v are?

    Thanks,

    Laura


    On Sat, Aug 23, 2008 at 11:41 AM, Robin Hankin <rksh1 at cam.ac.uk
    <mailto:rksh1 at cam.ac.uk>> wrote:

        Laura Bonnett wrote:

            crosstable[,,expand[d,1],expand[d,2],expand[d,3],...expand[d,n]]
             crosstable is just a crosstabulation of an
            n+2-dimensional dataset and I am trying to pick out those
            that are in combination 'd' of expand. So for example, for
            5-dimensional data using your example:
              Var1 Var2 Var3
            1     1    1    1
            2     2    1    1
            3     3    1    1
            4     1    2    1
            5     2    2    1
            6     3    2    1
            7     1    1    2
            8     2    1    2
            9     3    1    2
            10    1    2    2
            11    2    2    2
            12    3    2    2
             d refers to the row of the matrix above - d=2 is 2,1,1 so
            crosstable[,,2,1,1] would retrieve all the data where Var1
            =2, Var2=1, Var3=1 and the two remaining variables are
            given in the crosstabulations for all values.
             Is that any better?


        OK  I think I understand.  The magic package uses this type of
        construction extensively, but not this particular one.

        It's trickier than I'd have expected.

        Try this:

        f <- function(a,v){
          jj <-
        sapply(dim(a)[seq_len(length(dim(a))-length(v))],seq_len,simplify=FALSE)
          jj <- c(jj , as.list(v))
          do.call("[" , c(list(a) , jj, drop=TRUE))
        }



        [you will have to coerce the output from expand.grid() to a
        matrix in order to extract a row from it]


        HTH

        rksh








        -- 
        Robin K. S. Hankin
        Senior Research Associate
        Cambridge Centre for Climate Change Mitigation Research (4CMR)
        Department of Land Economy
        University of Cambridge
        rksh1 at cam.ac.uk <mailto:rksh1 at cam.ac.uk>
        01223-764877