dendrogram  R Documentation 
Class "dendrogram"
provides general functions for handling
treelike structures. It is intended as a replacement for similar
functions in hierarchical clustering and classification/regression
trees, such that all of these can use the same engine for plotting or
cutting trees.
as.dendrogram(object, ...) ## S3 method for class 'hclust' as.dendrogram(object, hang = 1, check = TRUE, ...) ## S3 method for class 'dendrogram' as.hclust(x, ...) ## S3 method for class 'dendrogram' plot(x, type = c("rectangle", "triangle"), center = FALSE, edge.root = is.leaf(x)  !is.null(attr(x,"edgetext")), nodePar = NULL, edgePar = list(), leaflab = c("perpendicular", "textlike", "none"), dLeaf = NULL, xlab = "", ylab = "", xaxt = "n", yaxt = "s", horiz = FALSE, frame.plot = FALSE, xlim, ylim, ...) ## S3 method for class 'dendrogram' cut(x, h, ...) ## S3 method for class 'dendrogram' merge(x, y, ..., height, adjust = c("auto", "add.max", "none")) ## S3 method for class 'dendrogram' nobs(object, ...) ## S3 method for class 'dendrogram' print(x, digits, ...) ## S3 method for class 'dendrogram' rev(x) ## S3 method for class 'dendrogram' str(object, max.level = NA, digits.d = 3, give.attr = FALSE, wid = getOption("width"), nest.lev = 0, indent.str = "", last.str = getOption("str.dendrogram.last"), stem = "", ...) is.leaf(object)
object 
any R object that can be made into one of class

x, y 
object(s) of class 
hang 
numeric scalar indicating how the height of leaves
should be computed from the heights of their parents; see

check 
logical indicating if 
type 
type of plot. 
center 
logical; if 
edge.root 
logical; if true, draw an edge to the root node. 
nodePar 
a 
edgePar 
a 
leaflab 
a string specifying how leaves are labeled. The
default 
dLeaf 
a number specifying the distance in user
coordinates between the tip of a leaf and its label. If 
horiz 
logical indicating if the dendrogram should be drawn horizontally or not. 
frame.plot 
logical indicating if a box around the plot should
be drawn, see 
h 
height at which the tree is cut. 
height 
height at which the two dendrograms should be merged. If not
specified (or 
adjust 
a string determining if the leaf values should be
adjusted. The default, 
xlim, ylim 
optional x and ylimits of the plot, passed to

..., xlab, ylab, xaxt, yaxt 
graphical parameters, or arguments for other methods. 
digits 
integer specifying the precision for printing, see

max.level, digits.d, give.attr, wid, nest.lev, indent.str 
arguments
to 
last.str, stem 
strings used for 
The dendrogram is directly represented as a nested list where each
component corresponds to a branch of the tree. Hence, the first
branch of tree z
is z[[1]]
, the second branch of the
corresponding subtree is z[[1]][[2]]
, or shorter
z[[c(1,2)]]
, etc.. Each node of the tree
carries some information needed for efficient plotting or cutting as
attributes, of which only members
, height
and
leaf
for leaves are compulsory:
members
total number of leaves in the branch
height
numeric nonnegative height at which the node is plotted.
midpoint
numeric horizontal distance of the node from
the left border (the leftmost leaf) of the branch (unit 1 between
all leaves). This is used for plot(*, center = FALSE)
.
label
character; the label of the node
x.member
for cut()$upper
,
the number of former members; more generally a substitute
for the members
component used for ‘horizontal’
(when horiz = FALSE
, else ‘vertical’) alignment.
edgetext
character; the label for the edge leading to the node
nodePar
a named list (of length1 components)
specifying nodespecific attributes for points
plotting, see the nodePar
argument above.
edgePar
a named list (of length1 components)
specifying attributes for segments
plotting of the
edge leading to the node, and drawing of the edgetext
if
available, see the edgePar
argument above.
leaf
logical, if TRUE
, the node is a leaf of
the tree.
cut.dendrogram()
returns a list with components $upper
and $lower
, the first is a truncated version of the original
tree, also of class dendrogram
, the latter a list with the
branches obtained from cutting the tree, each a dendrogram
.
There are [[
, print
, and str
methods for "dendrogram"
objects where the first one
(extraction) ensures that selecting subbranches keeps the class,
i.e., returns a dendrogram even if only a leaf.
On the other hand, [
(single bracket) extraction
returns the underlying list structure.
Objects of class "hclust"
can be converted to class
"dendrogram"
using method as.dendrogram()
, and since R
2.13.0, there is also a as.hclust()
method as an inverse.
rev.dendrogram
simply returns the dendrogram x
with
reversed nodes, see also reorder.dendrogram
.
The merge(x, y, ...)
method merges two or more
dendrograms into a new one which has x
and y
(and
optional further arguments) as branches. Note that before R 3.1.2,
adjust = "none"
was used implicitly, which is invalid when,
e.g., the dendrograms are from as.dendrogram(hclust(..))
.
nobs(object)
returns the total number of leaves (the
members
attribute, see above).
is.leaf(object)
returns logical indicating if object
is a
leaf (the most simple dendrogram).
plotNode()
and plotNodeLimit()
are helper functions.
Some operations on dendrograms such as merge()
make use of
recursion. For deep trees it may be necessary to increase
options("expressions")
: if you do, you are likely to need
to set the C stack size (Cstack_info()[["size"]]
) larger
than the default where possible.
plot()
:When using type = "triangle"
,
center = TRUE
often looks better.
str(d)
:If you really want to see the internal
structure, use str(unclass(d))
instead.
dendrapply
for applying a function to each node.
order.dendrogram
and reorder.dendrogram
;
further, the labels
method.
require(graphics); require(utils) hc < hclust(dist(USArrests), "ave") (dend1 < as.dendrogram(hc)) # "print()" method str(dend1) # "str()" method str(dend1, max.level = 2, last.str = "'") # only the first two sublevels oo < options(str.dendrogram.last = "\\") # yet another possibility str(dend1, max.level = 2) # only the first two sublevels options(oo) # .. resetting them op < par(mfrow = c(2,2), mar = c(5,2,1,4)) plot(dend1) ## "triangle" type and show inner nodes: plot(dend1, nodePar = list(pch = c(1,NA), cex = 0.8, lab.cex = 0.8), type = "t", center = TRUE) plot(dend1, edgePar = list(col = 1:2, lty = 2:3), dLeaf = 1, edge.root = TRUE) plot(dend1, nodePar = list(pch = 2:1, cex = .4*2:1, col = 2:3), horiz = TRUE) ## simple test for as.hclust() as the inverse of as.dendrogram(): stopifnot(identical(as.hclust(dend1)[1:4], hc[1:4])) dend2 < cut(dend1, h = 70) ## leaves are wrong horizontally in R 4.0 and earlier: plot(dend2$upper) plot(dend2$upper, nodePar = list(pch = c(1,7), col = 2:1)) ## dend2$lower is *NOT* a dendrogram, but a list of .. : plot(dend2$lower[[3]], nodePar = list(col = 4), horiz = TRUE, type = "tr") ## "inner" and "leaf" edges in different type & color : plot(dend2$lower[[2]], nodePar = list(col = 1), # non empty list edgePar = list(lty = 1:2, col = 2:1), edge.root = TRUE) par(op) d3 < dend2$lower[[2]][[2]][[1]] stopifnot(identical(d3, dend2$lower[[2]][[c(2,1)]])) str(d3, last.str = "'") ## to peek at the inner structure "if you must", use '[..]' indexing : str(d3[2][[1]]) ## or the full str(d3[]) ## merge() to join dendrograms: (d13 < merge(dend2$lower[[1]], dend2$lower[[3]])) ## merge() all parts back (using default 'height' instead of original one): den.1 < Reduce(merge, dend2$lower) ## or merge() all four parts at same height > 4 branches (!) d. < merge(dend2$lower[[1]], dend2$lower[[2]], dend2$lower[[3]], dend2$lower[[4]]) ## (with a warning) or the same using do.call : stopifnot(identical(d., do.call(merge, dend2$lower))) plot(d., main = "merge(d1, d2, d3, d4) > dendrogram with a 4split") ## "Zoom" in to the first dendrogram : plot(dend1, xlim = c(1,20), ylim = c(1,50)) nP < list(col = 3:2, cex = c(2.0, 0.75), pch = 21:22, bg = c("light blue", "pink"), lab.cex = 0.75, lab.col = "tomato") plot(d3, nodePar= nP, edgePar = list(col = "gray", lwd = 2), horiz = TRUE) addE < function(n) { if(!is.leaf(n)) { attr(n, "edgePar") < list(p.col = "plum") attr(n, "edgetext") < paste(attr(n,"members"),"members") } n } d3e < dendrapply(d3, addE) plot(d3e, nodePar = nP) plot(d3e, nodePar = nP, leaflab = "textlike")
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