R help - Jul 2004 - vectorizing a matrix computation

Dear R users

I have a 4-dimensional matrix (actually several 3d (x,y, slices) 
matrices appended over time (volumes))

say, e.g. I want to z-transform the data (subtract the mean and divide 
by the std-deviation)

for (slice in 1:slices) {
     for (x in 1:x.dim) {
         for (y in 1:y.dim) {
         t <- as.matrix(my.matrix[x,y,slice,1:volumes])
         for (vol in 1:volumes) {
             my.matrix.transformed[x,y,slice,vol] <- 
(my.matrix[x,y,slice,vol] - mean(t))/sqrt(var(t))
             }
         }
     }
}

how can I vectorize such a function using, one of the *apply functions?

many thanks

Cheers

Christoph

Hallo Christoph!

Using apply and sweep.
Both of them accept  as the second argument (MARGIN) a vector which specifies
the dimension.

?apply
?sweep.

To specify the subscripts accurately I always need some trials, and to run
tests, so I cant you provide with the final solution.

Hope it helps anyway.

Sincerely Eryk.



*********** REPLY SEPARATOR  ***********

On 7/20/2004 at 11:31 AM Christoph Lehmann wrote:
>>>Dear R users
>>>
>>>I have a 4-dimensional matrix (actually several 3d (x,y, slices) 
>>>matrices appended over time (volumes))
>>>
>>>say, e.g. I want to z-transform the data (subtract the mean and
divide
>>>by the std-deviation)
>>>
>>>for (slice in 1:slices) {
>>>     for (x in 1:x.dim) {
>>>         for (y in 1:y.dim) {
>>>         t <- as.matrix(my.matrix[x,y,slice,1:volumes])
>>>         for (vol in 1:volumes) {
>>>             my.matrix.transformed[x,y,slice,vol] <- 
>>>(my.matrix[x,y,slice,vol] - mean(t))/sqrt(var(t))
>>>             }
>>>         }
>>>     }
>>>}
>>>
>>>how can I vectorize such a function using, one of the *apply
functions?
>>>
>>>many thanks
>>>
>>>Cheers
>>>
>>>Christoph
>>>
>>>______________________________________________
>>>R-help at stat.math.ethz.ch mailing list
>>>https://www.stat.math.ethz.ch/mailman/listinfo/r-help
>>>PLEASE do read the posting guide!
http://www.R-project.org/posting-guide.html


Dipl. bio-chem. Eryk Witold Wolski    @    MPI-Moleculare Genetic   
Ihnestrasse 63-73 14195 Berlin       'v'    
tel: 0049-30-83875219               /   \    
mail: wolski at molgen.mpg.de        ---W-W----   
http://www.molgen.mpg.de/~wolski

I think this should do:

z <- apply(my.matrix, 1:3, scale)
z <- aperm(z, c(2:4, 1))

Andy
> From: Christoph Lehmann
> 
> Dear R users
> 
> I have a 4-dimensional matrix (actually several 3d (x,y, slices) 
> matrices appended over time (volumes))
> 
> say, e.g. I want to z-transform the data (subtract the mean 
> and divide 
> by the std-deviation)
> 
> for (slice in 1:slices) {
>      for (x in 1:x.dim) {
>          for (y in 1:y.dim) {
>          t <- as.matrix(my.matrix[x,y,slice,1:volumes])
>          for (vol in 1:volumes) {
>              my.matrix.transformed[x,y,slice,vol] <- 
> (my.matrix[x,y,slice,vol] - mean(t))/sqrt(var(t))
>              }
>          }
>      }
> }
> 
> how can I vectorize such a function using, one of the *apply 
> functions?
> 
> many thanks
> 
> Cheers
> 
> Christoph
> 
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://www.stat.math.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide! 
> http://www.R-project.org/posting-guide.html
> 
>