Nothing

```
### Casts a vegan spantree object into single linkage dendrogram of
### class hclust. The non-trivial items in "hclust" object are a
### 'merge' matrix for fusions of points and/or clusters, a 'height'
### vector which gives the heights of each fusion, and an 'order'
### vector that gives the order of leaves in the plotted
### dendrogram. The 'height's are only sorted spantree segment
### distances, but for 'merge' we need to establish cluster
### memberships, and for 'order' we must traverse the tree.
`as.hclust.spantree` <-
function(x, ...)
{
## Order by the lengths of spanning tree links
o <- order(x$dist)
npoints <- x$n
if(npoints < 2)
stop("needs at least two points")
## Ordered indices of dads and kids
dad <- (2:npoints)[o]
kid <- x$kid[o]
## merge matrix of hclust has negative index when a single point
## is added to a tree and a positive index when a group is joined
## to a tree, and the group is numbered by the level it was
## formed.
labs <- -seq_len(npoints)
merge <- matrix(0, nrow=npoints-1, ncol=2)
for(i in 1:nrow(merge)) {
merge[i, ] <- c(labs[dad[i]], labs[kid[i]])
## update labs for the current group and its kids
labs[labs %in% labs[c(dad[i], kid[i])]] <- i
}
order <- hclustMergeOrder(merge)
out <- list(merge = merge, height = x$dist[o], order = order,
labels = x$labels, method = "spantree", call =
match.call())
class(out) <- "hclust"
out
}
### Internal vegan function to get the 'order' from a merge matrix of
### an hclust tree
`hclustMergeOrder` <-
function(merge)
{
## Get order of leaves with recursive search from the root
order <- numeric(nrow(merge)+1)
ind <- 0
## "<<-" updates data only within hclustMergeOrder, but outside
## the visit() function.
visit <- function(i, j) {
if (merge[i,j] < 0) {
ind <<- ind+1
order[ind] <<- -merge[i,j]
} else {
visit(merge[i,j], 1)
visit(merge[i,j], 2)
}
}
visit(nrow(merge), 1)
visit(nrow(merge), 2)
return(order)
}
### Reorder an hclust tree. Basic R provides reorder.dendrogram, but
### this functoin works with 'hclust' objects, and also differs in
### implementation. We use either weighted mean, min or max or
### sum. The dendrogram is always ordered in ascending order, so that
### with max the left kid always has lower value. So with 'max' the
### largest value is smaller in leftmost group. The choice 'sum'
### hardly makes sense, but it is the default in
### reorder.dendrogram. The ordering with 'mean' differs from
### reorder.dendrogram which uses unweighted means, but here we weight
### means by group sizes so that the mean of an internal node is the
### mean of its leaves.
`reorder.hclust` <-
function(x, wts,
agglo.FUN = c("mean", "min", "max", "sum", "uwmean"),
...)
{
agglo.FUN <- match.arg(agglo.FUN)
merge <- x$merge
nlev <- nrow(merge)
stats <- numeric(nlev)
counts <- numeric(nlev)
pair <- numeric(2)
pairw <- numeric(2)
## Go through merge, order each level and update the statistic.
for(i in 1:nlev) {
for(j in 1:2) {
if (merge[i,j] < 0) {
pair[j] <- wts[-merge[i,j]]
pairw[j] <- 1
} else {
pair[j] <- stats[merge[i,j]]
pairw[j] <- counts[merge[i,j]]
}
}
## reorder
merge[i,] <- merge[i, order(pair)]
## statistic for this merge level
stats[i] <-
switch(agglo.FUN,
"mean" = weighted.mean(pair, pairw),
"min" = min(pair),
"max" = max(pair),
"sum" = sum(pair),
"uwmean" = mean(pair))
counts[i] <- sum(pairw)
}
## Get the 'order' of the reordered dendrogram
order <- hclustMergeOrder(merge)
x$merge <- merge
x$order <- order
x$value <- stats
x
}
### Trivial function to reverse the order of an hclust tree (why this
### is not in base R?)
`rev.hclust` <-
function(x)
{
x$order <- rev(x$order)
x
}
### Get coordinates for internal or terminal nodes (leaves) that would
### be used in plot.hclust
`scores.hclust` <-
function(x, display = "internal", ...)
{
extnam <- c("leaves", "terminal")
intnam <- c("internal")
display <- match.arg(display, c(extnam, intnam))
## Terminal nodes (leaves): plot.hclust scales x-axis for n points
## as 1..n. The y-value is the 'height' where the terminal node
## was fused to the tree.
if(display %in% extnam) {
merge <- x$merge
y <- numeric(nrow(merge) + 1)
for(i in 1:nrow(merge))
for(j in 1:2)
if(merge[i,j] < 0)
y[-merge[i,j]] <- x$height[i]
xx <- order(x$order)
xy <- cbind(`x` = xx, `height` = y)
} else {
## Internal nodes are given in the order they were fused which
## also is the order of 'height'
xx <- reorder(x, order(x$order), agglo.FUN = "uwmean")$value
xy <- cbind(`x`= xx, `height` = x$height)
}
xy
}
```

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