cluster (version 2.1.8)

plot.diana: Plots of a Divisive Hierarchical Clustering

Description

Creates plots for visualizing a diana object.

Usage

# S3 method for diana
plot(x, ask = FALSE, which.plots = NULL, main = NULL,
           sub = paste("Divisive Coefficient = ", round(x$dc, digits = 2)),
           adj = 0, nmax.lab = 35, max.strlen = 5, xax.pretty = TRUE, ...)

Arguments

x

an object of class "diana", typically created by diana(.).

ask

logical; if true and which.plots is NULL, plot.diana operates in interactive mode, via menu.

which.plots

integer vector or NULL (default), the latter producing both plots. Otherwise, which.plots must contain integers of 1 for a banner plot or 2 for a dendrogram or “clustering tree”.

main, sub

main and sub title for the plot, each with a convenient default. See documentation for these arguments in plot.default.

adj

for label adjustment in bannerplot().

nmax.lab

integer indicating the number of labels which is considered too large for single-name labelling the banner plot.

max.strlen

positive integer giving the length to which strings are truncated in banner plot labeling.

xax.pretty

logical or integer indicating if pretty(*, n = xax.pretty) should be used for the x axis. xax.pretty = FALSE is for back compatibility.

...

graphical parameters (see par) may also be supplied and are passed to bannerplot() or pltree(), respectively.

Side Effects

An appropriate plot is produced on the current graphics device. This can be one or both of the following choices:
Banner
Clustering tree

Details

When ask = TRUE, rather than producing each plot sequentially, plot.diana displays a menu listing all the plots that can be produced. If the menu is not desired but a pause between plots is still wanted one must set par(ask= TRUE) before invoking the plot command.

The banner displays the hierarchy of clusters, and is equivalent to a tree. See Rousseeuw (1986) or chapter 6 of Kaufman and Rousseeuw (1990). The banner plots the diameter of each cluster being splitted. The observations are listed in the order found by the diana algorithm, and the numbers in the height vector are represented as bars between the observations.

The leaves of the clustering tree are the original observations. A branch splits up at the diameter of the cluster being splitted.

References

see those in plot.agnes.

See Also

diana, diana.object, twins.object, par.

Examples

example(diana)# -> dv <- diana(....)

plot(dv, which = 1, nmax.lab = 100)

## wider labels :
op <- par(mar = par("mar") + c(0, 2, 0,0))
plot(dv, which = 1, nmax.lab = 100, max.strlen = 12)
par(op)