uhoh, missed two lines on the top.Sorry about that.
the whole code looks like this.
nchars = 4
maxvals = c(2,2,2,2)
tmp = 0:(maxvals[1])
for(i in 2:nchars) {
tmp <- outer(tmp, 0:(maxvals[i]), FUN="paste", sep=".")
}
states = tmp
stateidx = array(1:length(states), dim=dim(states))
transition <- matrix(data=0, nrow=length(states), ncol=length(states))
findstatedim <- function(x) which(stateidx==x, arr.ind = TRUE)
manhattandistance <- function(x,y) sum(abs(findstatedim(x)-findstatedim(y)))
for(i in 1:length(states)) {
for (j in 1:length(states)) {
if (manhattandistance(i, j)==1) {
if (sum(findstatedim(i)-findstatedim(j)) < 0) {
transition[i,j] = "gain"
if (findstatedim(i)[findstatedim(i)-findstatedim(j) == -1] == 1)
{
transition[i,j] = "firstgain"
}
}
else {
transition[i,j] = "loss"
}
}
}
}
transition
On Thu, May 7, 2009 at 2:54 PM, miraceti <mirac...@gmail.com> wrote:
> Hi, I am still not familiar with vectorization.
> Could you help with making this for loop more efficient?
> The code is trying to make a Q matrix for a multidimensional state space
> with specific conditions.
>
> thanks
> Mira
>
>
> tmp = 0:(maxvals[1])
> for(i in 2:nchars) {
> tmp <- outer(tmp, 0:(maxvals[i]), FUN="paste", sep=".")
> }
> states = tmp
> stateidx = array(1:length(states), dim=dim(states))
> transition <- matrix(data=0, nrow=length(states), ncol=length(states))
>
> findstatedim <- function(x) which(stateidx==x, arr.ind = TRUE)
> manhattandistance <- function(x,y)
> sum(abs(findstatedim(x)-findstatedim(y)))
>
> for(i in 1:length(states)) {
> for (j in 1:length(states)) {
> if (manhattandistance(i, j)==1) {
> if (sum(findstatedim(i)-findstatedim(j)) < 0) {
> transition[i,j] = "gain"
> if (findstatedim(i)[findstatedim(i)-findstatedim(j) == -1] ==
> 1) {
> transition[i,j] = "firstgain"
> }
> }
> else {
> transition[i,j] = "loss"
> }
> }
> }
> }
> transition
>
>
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