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stress <- function(Dx, Dy) {
if (any(Dx != t(Dx)) || any(Dy != t(Dy))) {
stop("Dx and Dy must be symmetric")
}
Dx <- as.matrix(Dx)
Dy <- as.matrix(Dy)
if (nrow(Dx) != nrow(Dy)) {
stop("Dx and Dy must have the same number of elements")
}
n <- nrow(Dx)
s <- vector("numeric", n)
for (i in 1:n) {
s[i] <- 0
for (j in 1:n) {
if (i == j) {
next
}
s[i] = s[i] + (Dx[i, j] - Dy[i, j])^2 / Dx[i, j]
}
s[i] = s[i] / sum(D[i, ])
}
s
}
NP <- function(Dx, Dy, k = 9) {
if (any(Dx != t(Dx)) || any(Dy != t(Dy))) {
stop("Dx and Dy must be symmetric")
}
Dx <- as.matrix(Dx)
Dy <- as.matrix(Dy)
if (nrow(Dx) != nrow(Dy)) {
stop("Dx and Dy must have the same number of elements")
}
n <- nrow(Dx)
if (k >= n) {
stop("k must be smaller than the number of elements")
}
preservation <- vector("numeric", n)
for (i in 1:n) {
nx <- order(Dx[i, ])[1 + 1:k]
ny <- order(Dy[i, ])[1 + 1:k]
diff <- setdiff(nx, ny)
preservation[i] <- (k - length(diff)) / k
}
preservation
}
d2p <- function(D, sigmas) {
if (any(D != t(D))) {
stop("D must be symmetric")
}
D <- as.matrix(D)
n <- nrow(D)
P <- matrix(data=NA, nrow=nrow(D), ncol=ncol(D))
for (i in 1:n) {
denom <- sum(exp(-D[i, ] / sigmas))
P[i, ] <- exp(-D[i, ] / sigmas) / denom
}
P
}
klDivergence <- function(P, Q) {
if (nrow(P) != ncol(P) || nrow(Q) != ncol(Q)) {
stop("P and Q must be square")
}
if (nrow(P) != nrow(Q)) {
stop("P and Q must have the same number of elements")
}
n <- nrow(P)
d <- vector("numeric", n)
for (i in 1:n) {
d[i] <- sum(P[i, ] * log(P[i, ] / Q[i, ]))
}
d
}
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