\HeaderA{plot.partition}{Plot of a Partition of the Data Set}{plot.partition}
\keyword{cluster}{plot.partition}
\keyword{hplot}{plot.partition}
\begin{Description}\relax
Creates plots for visualizing a \code{partition} object.
\end{Description}
\begin{Usage}
\begin{verbatim}
## S3 method for class 'partition':
plot(x, ask = FALSE, which.plots = NULL,
               nmax.lab = 40, max.strlen = 5, data = x$data, dist = NULL,
               cor = TRUE, stand = FALSE, lines = 2,
               shade = FALSE, color = FALSE, labels = 0, plotchar = TRUE,
               span = TRUE, xlim = NULL, ylim = NULL, main = NULL, ...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] an object of class \code{"partition"}, typically created by the
functions \code{\LinkA{pam}{pam}}, \code{\LinkA{clara}{clara}}, or \code{\LinkA{fanny}{fanny}}.
\item[\code{ask}] logical; if true and \code{which.plots} is \code{NULL},
\code{plot.partition} operates in interactive mode, via \code{\LinkA{menu}{menu}}.
\item[\code{which.plots}] integer vector or NULL (default), the latter
producing both plots.  Otherwise, \code{which.plots} must contain
integers of \code{1} for a \emph{clusplot} or \code{2} for
\emph{silhouette}.
\item[\code{nmax.lab}] integer indicating the number of labels which is
considered too large for single-name labeling the silhouette plot.
\item[\code{max.strlen}] positive integer giving the length to which
strings are truncated in silhouette plot labeling.
\item[\code{data}] numeric matrix with the scaled data; per default taken
from the partition object \code{x}, but can be specified explicitly.
\item[\code{dist}] when \code{x} does not have a \code{diss} component as for
\code{\LinkA{pam}{pam}(*, keep.diss=FALSE)}, \code{dist} must be the
dissimilarity if a clusplot is desired.
\item[\code{cor,stand,lines,shade,color,labels,plotchar,span,xlim,ylim,main, ...}] All optional arguments available for the \code{\LinkA{clusplot.default}{clusplot.default}}
function (except for the \code{diss} one) and graphical parameters
(see \code{\LinkA{par}{par}}) may also be supplied as arguments to this function.
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
When \code{ask= TRUE}, rather than producing each plot sequentially,
\code{plot.partition} 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,
call \code{par(ask= TRUE)} before invoking the plot command.

The \emph{clusplot} of a cluster partition consists of a two-dimensional
representation of the observations, in which the clusters are
indicated by ellipses (see \code{\LinkA{clusplot.partition}{clusplot.partition}} for more
details).

The \emph{silhouette plot} of a nonhierarchical clustering is fully
described in Rousseeuw (1987) and in chapter 2 of Kaufman and
Rousseeuw (1990).
For each observation i, a bar is drawn, representing its silhouette
width s(i), see \code{\LinkA{silhouette}{silhouette}} for details.
Observations are grouped per cluster, starting with cluster 1 at the
top.  Observations with a large s(i) (almost 1) are very well
clustered, a small s(i) (around 0) means that the observation lies
between two clusters, and observations with a negative s(i) are
probably placed in the wrong cluster.

A clustering can be performed for several values of \code{k} (the number of
clusters).  Finally, choose the value of \code{k} with the largest overall
average silhouette width.
\end{Details}
\begin{Section}{Side Effects}
An appropriate plot is produced on the current graphics device.  This
can be one or both of the following choices:
\\ Clusplot
\\ Silhouette plot
\end{Section}
\begin{Note}\relax
In the silhouette plot, observation labels are only printed when the
number of observations is less than \code{nmax.lab} (40, by default),
for readability.  Moreover, observation labels are truncated to
maximally \code{max.strlen} (5) characters.  \\
For more flexibility, use \code{plot(silhouette(x), ...)}, see
\code{\LinkA{plot.silhouette}{plot.silhouette}}.
\end{Note}
\begin{References}\relax
Rousseeuw, P.J. (1987)
Silhouettes: A graphical aid to the interpretation and validation of
cluster analysis. \emph{J. Comput. Appl. Math.}, \bold{20}, 53--65.

Further, the references in \code{\LinkA{plot.agnes}{plot.agnes}}.
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{partition.object}{partition.object}}, \code{\LinkA{clusplot.partition}{clusplot.partition}},
\code{\LinkA{clusplot.default}{clusplot.default}}, \code{\LinkA{pam}{pam}},
\code{\LinkA{pam.object}{pam.object}}, \code{\LinkA{clara}{clara}},
\code{\LinkA{clara.object}{clara.object}}, \code{\LinkA{fanny}{fanny}},
\code{\LinkA{fanny.object}{fanny.object}}, \code{\LinkA{par}{par}}.
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
## generate 25 objects, divided into 2 clusters.
x <- rbind(cbind(rnorm(10,0,0.5), rnorm(10,0,0.5)),
           cbind(rnorm(15,5,0.5), rnorm(15,5,0.5)))
plot(pam(x, 2))

## Save space not keeping data in clus.object, and still clusplot() it:
data(xclara)
cx <- clara(xclara, 3, keep.data = FALSE)
cx$data # is NULL
plot(cx, data = xclara)
\end{ExampleCode}
\end{Examples}