Nothing
# shrinking clusters
shrinking <- function(y, K, disMethod = "Euclidean",
eps = 1.0e-4, itmax = 20)
{
disMethod = match.arg(disMethod, c("Euclidean", "1-corr"))
if(!is.matrix(y))
{ y <- matrix(y, ncol = 1) }
y <- as.matrix(y)
n <- nrow(y)
p <- ncol(y)
if(disMethod == "Euclidean") {
disMethod2 <- 1
} else { #if (disMethod == "corr") {
disMethod2 <- 2
}
K2 <- K + 1
ynew <- matrix(0, nrow = n, ncol = p)
res <- .Fortran("sharpen",
as.double(y),
as.integer(n),
as.integer(p),
as.integer(K2),
as.integer(K),
as.integer(itmax),
as.double(eps),
as.integer(disMethod2),
ynew = as.double(ynew),
PACKAGE = "clues")
# Like R, Fortran stores a matrix by columns
y.new <- matrix(res$ynew, nrow = n, ncol = p, byrow = FALSE)
invisible(y.new)
}
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