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library(methods)
frame.files <- lapply(sys.frames(), function(x) x$ofile)
frame.files <- Filter(Negate(is.null), frame.files)
script.dir <- normalizePath(dirname(frame.files[[length(frame.files)]]))
source.file <- paste(script.dir, '/', 'RSyncRNG.so', sep='')
dyn.load(source.file)
SyncRNG <- setRefClass('SyncRNG',
fields=list(
seed='numeric',
state='numeric',
BPF='numeric'
),
methods=list(
initialize=function(..., seed=0) {
BPF <<- 32
seed <<- seed
tmp <- .Call('R_syncrng_seed',
as.numeric(seed))
state <<- tmp[1:4]
callSuper(...)
},
randi=function() {
tmp <- .Call('R_syncrng_rand',
as.numeric(state))
state <<- tmp[1:4]
return(tmp[5])
},
rand=function() {
r <- randi()
return (r * 2.3283064365387e-10)
},
randbelow=function(n) {
maxsize <- 2^BPF
if (n >= maxsize) {
warning(paste("Underlying random generator ",
"does not supply\n enough bits ",
"to choose from a population ",
"range this large.\n"))
return(round(rand() * n))
}
rem <- maxsize %% n
limit <- (maxsize - rem) / maxsize
r <- rand()
while (r >= limit)
r <- rand()
return(round(r*maxsize) %% n)
},
shuffle=function(x) {
y <- x
for (i in rev(1:(length(y)-1))) {
j <- randbelow(i+1)
tmp <- y[i+1]
y[i+1] <- y[j+1]
y[j+1] <- tmp
}
return(y)
}
)
)
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