Ben,
You can use the sample() function to randomly add -1, 0, or 1 to each
observation, and control for the probability of mutation at the same time.
Then you can use the match() function to make sure that any mutations in
X are carried through to Y in the same way. I wrote the function to do
each list element separately. So a gene in X[[1] and Y[[1]] will be
mutated in the same way, but the same gene in X[[2]] and Y[[2]] may be
mutated in a different way. Not sure if that is what you want.
Mutate <- function(x, y, prob.mutate=0.9) {
ux <- unique(c(x, y))
new.ux <- ux + sample(c(-1, 0, 1), size=length(ux), replace=TRUE,
prob=c(prob.mutate/2, 1-prob.mutate, prob.mutate/2))
new.x <- new.ux[match(x, ux)]
new.y <- new.ux[match(y, ux)]
list(xm=new.x, ym=new.y)
}
Effectors <- lapply(seq(X), function(i) Mutate(X[[i]], Y[[i]]))
Jean
"Benjamin Ward (ENV)" <b.w...@uea.ac.uk> wrote on 11/27/2012 10:45:23 AM:
>
> Hi,
>
> I have the following data:
>
> Path_Number <- 5
> ID.Path <- c(1:Path_Number) # Make vector of ID's.
> No_of_X <- sample(50:550, length(ID.Path), replace=TRUE) #
> X <- split(sample(1:10000, sum(No_of_X), replace=TRUE),
rep(ID.Path,No_of_X))
> Y <- lapply(X,function(x) sample(x, round(runif(1, min=10, max=50))))
>
> X and Y are both lists, and I've made the following function to work
> on that data as part of a simulation I'm building:
>
> Mutate<-function(x){
> l<-0
> for(i in x){
> l2<-0
> l<-l+1
> for(i in x[[l]]){
> l2<-l2+1
> if(runif(1) < 0.9) ifelse(runif(1) <0.5, x[[l]][l2] <- x[[l]]
> [l2]+1, x[[l]][l2] <- x[[l]][l2]-1)
> }
> }
> return(x)
> }
>
> I call this with Effectors<-Mutate(X)
> The function is designed to alter the values of each element in X by
> either + or - 1 (50:50 chance wether + or -). However Y, elements of
> which are a subset of the corresponding elements of X, need to be
> consistent i.e. if a value in X is changed, and that value is part
> of the Y subset, then the value in Y also needs to be changed.
> however, since Y is a smaller subset it will not be indexed the
> same. My idea was to include in the function an if statement that
> checks if Y contains the value to be changed, removes it, and then
> after the value in X is changed, put the new value in Y. I attemptedthis
with:
>
>
> Mutate<-function(x,y){
> l<-0
> for(i in x){
> l2<-0
> l<-l+1
> for(i in x[[l]]){
> l2<-l2+1
> if(runif(1) < 0.9){
> if(x[[l]][l2] %in% y[[l]] == TRUE){
> y[[l]]<-[which(y[[l]]!=x[[l]][l2])]
> if(runif(1) <0.5){
> x[[l]][l2] <- x[[l]][l2]+1
> y[[l]]<-append(x[[l]][l2])
> }else{
> x[[l]][l2] <- x[[l]][l2]-1
> y[[l]]<-append(x[[l]][l2])
> }
> }
> ifelse(runif(1) <0.5, x[[l]][l2] <- x[[l]][l2]+1, x[[l]][l2]
> <- x[[l]][l2]-1)
> }
> }
> }
> return(list(x,y))
> }
>
> Bit of an eyesore so I've put the altered stuff in bold. I've
> basically taken what the ifelse statement does in the first
> function, (which is still there and run if Y does not contain the X
> value being altered) and broken it down into an if and an else
> segment with multiple operations in curly braces to accommodate the
> extra actions needed to alter Y as well as X. This was all I could
> think of to keep changes between the two "in sync", however this
> does not work when I try to load the function into workspace:
>
> Error: unexpected '}' in "}"
>
> I hope someone can point out what it is I've done that isn't
> working, or a better way to do this.
>
> Best Wishes,
>
> Ben W.
>
> UEA (ENV) & The Sainsbury Laboratory.
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