R/permutations.R

In BayHap: Bayesian analysis of haplotype association using Markov Chain Monte Carlo

`permutations` <-
function (n, r, v = 1:n, set = TRUE, repeats.allowed = FALSE) 
{
    if (mode(n) != "numeric" || length(n) != 1 || n < 1 || (n%%1) != 
        0) 
        stop("bad value of n")
    if (mode(r) != "numeric" || length(r) != 1 || r < 1 || (r%%1) != 
        0) 
        stop("bad value of r")
    if (!is.atomic(v) || length(v) < n) 
        stop("v is either non-atomic or too short")
    if ((r > n) & repeats.allowed == FALSE) 
        stop("r > n and repeats.allowed=FALSE")
    if (set) {
        v <- unique(sort(v))
        if (length(v) < n) 
            stop("too few different elements")
    }
    v0 <- vector(mode(v), 0)
    if (repeats.allowed) 
        sub <- function(n, r, v) {
            if (r == 1) 
                matrix(v, n, 1)
            else if (n == 1) 
                matrix(v, 1, r)
            else {
                inner <- Recall(n, r - 1, v)
                cbind(rep(v, rep(nrow(inner), n)), matrix(t(inner), 
                  ncol = ncol(inner), nrow = nrow(inner) * n, 
                  byrow = TRUE))
            }
        }
    else sub <- function(n, r, v) {
        if (r == 1) 
            matrix(v, n, 1)
        else if (n == 1) 
            matrix(v, 1, r)
        else {
            X <- NULL
            for (i in 1:n) X <- rbind(X, cbind(v[i], Recall(n - 
                1, r - 1, v[-i])))
            X
        }
    }
    sub(n, r, v[1:n])
}