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## Ordimedian finds the spatial medians for groups. Spatial medians
## are L1 norms or statistics that minimize sum of distances of points
## from the statistic and 1d they are the medians. The current
## algorithm minimizes the L1 norm with optim and is pretty
## inefficient. Package ICSNP has a better algorithm (and we may steal
## it from them later).
`ordimedian` <-
function(ord, groups, display = "sites", label = FALSE, ...)
{
## Sum of distances from the statistic
medfun <-
function(x, ord) sum(sqrt(rowSums(sweep(ord, 2, x)^2)),
na.rm = TRUE)
## derivative of medfun (if NULL, optim will use numerical
## differentiation)
dmedfun <- function(x, ord) {
up <- -sweep(ord, 2, x)
dn <- sqrt(rowSums(sweep(ord, 2, x)^2))
colSums(sweep(up, 1, dn, "/"))
}
#dmedfun <- NULL
pts <- scores(ord, display = display, ...)
inds <- names(table(groups))
medians <- matrix(NA, nrow = length(inds), ncol = ncol(pts))
rownames(medians) <- inds
colnames(medians) <- colnames(pts)
for (i in inds) {
X <- pts[groups == i, , drop = FALSE]
if (NROW(X) > 0)
medians[i, ] <- optim(apply(X, 2, median, na.rm = TRUE),
fn = medfun, gr = dmedfun,
ord = X, method = "BFGS")$par
if(label)
ordiArgAbsorber(medians[i,1], medians[i,2], label = i,
FUN = text, ...)
}
invisible(medians)
}
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