plot {apcluster}  R Documentation 
Plot Clustering Results
Description
Functions for Visualizing Clustering Results
Usage
## S4 method for signature 'APResult,missing'
plot(x, y, type=c("netsim", "dpsim", "expref"),
xlab="# Iterations", ylab="Similarity", ...)
## S4 method for signature 'ExClust,matrix'
plot(x, y, connect=TRUE, xlab="", ylab="",
labels=NA, limitNo=15, ...)
## S4 method for signature 'ExClust,data.frame'
plot(x, y, connect=TRUE, xlab="",
ylab="", labels=NA, limitNo=15, ...)
## S4 method for signature 'AggExResult,missing'
plot(x, y, main="Cluster dendrogram",
xlab="", ylab="", ticks=4, digits=2, base=0.05, showSamples=FALSE,
horiz=FALSE, ...)
## S4 method for signature 'AggExResult,matrix'
plot(x, y, k=NA, h=NA, ...)
## S4 method for signature 'AggExResult,data.frame'
plot(x, y, k=NA, h=NA, ...)
Arguments
x 
a clustering result object of class

y 
a matrix or data frame (see details below) 
type 
a string or array of strings indicating which
performance measures should be plotted; valid values are

xlab , ylab 
labels for axes of 2D plots; ignored if 
labels 
names used for variables in scatter plot matrix
(displayed if 
limitNo 
if the number of columns/features in 
connect 
used only if clustering is plotted on original data,
ignored otherwise. If 
main 
title of plot 
ticks 
number of ticks used for the axis on the left side of the plot (applies to dendrogram plots only, see below) 
digits 
number of digits used for the axis tickmarks on the left side of the plot (applies to dendrogram plots only, see below) 
base 
fraction of height used for the very first join; defaults to 0.05, i.e. the first join appears at 5% of the total height of the dendrogram. 
showSamples 
if 
horiz 
if 
k 
level to be selected when plotting a single clustering
level of cluster hierarchy (i.e. the number of clusters; see

h 
cutoff to be used when plotting a single clustering
level of cluster hierarchy (see 
... 
all other arguments are passed to the plotting command that
are used internally, 
Details
If plot
is called for an APResult
object
without specifying the second argument y
,
a plot is created that displays graphs of performance
measures over execution time of the affinity propagation run.
This only works if apcluster
was called with
details=TRUE
.
If plot
is called for an APResult
object
along with a matrix or data frame as argument y
, then the dimensions of
the matrix determine the behavior of plot
:
If the matrix
y
has two columns,y
is interpreted as the original data set. Then a plot of the clustering result superimposed on the original data set is created. Each cluster is displayed in a different color. The exemplar of each cluster is highlighted by a black square. Ifconnect
isTRUE
, lines connecting the cluster members to their exemplars are drawn. This variant ofplot
does not return any value.If
y
has more than two columns, clustering results are superimposed in a sort of scatter plot matrix. The variant thaty
is interpreted as similarity matrix if it is quadratic has been removed in version 1.3.2. Useheatmap
instead.If
y
has only one column, an error is displayed.
If plot
is called for an ExClust
object
along with a matrix or data frame as argument y
, then
plot
behaves exactly the same as described in the previous
paragraph.
If plot
is called for an AggExResult
object
without specifying the second argument y
, then a dendrogram
plot is drawn. This variant returns an invisible
dendrogram
object. The showSamples
argument
determines whether a complete dendrogram or a dendrogram of clusters
is plotted (see above). If the option horiz=TRUE
is used, the
dendrogram is rotated. Note that, in this case, the margin to the
right of the plot may not be wide enough to accommodate long
cluster/sample labels. In such a case, the figure margins have to
be widened before plot
is called.
If plot
is called for an AggExResult
object
along with a matrix or data frame y
, y
is
again interpreted
as original data set. If one of the two arguments k
or
h
is present, a clustering is cut out from the cluster hierarchy
using cutree
and this clustering is displayed with the
original data set as described above. This variant of
plot
returns an invisible ExClust
object
containing the extracted clustering.
Value
see details above
Author(s)
Ulrich Bodenhofer, Andreas Kothmeier & Johannes Palme apcluster@bioinf.jku.at
References
http://www.bioinf.jku.at/software/apcluster/
Bodenhofer, U., Kothmeier, A., and Hochreiter, S. (2011) APCluster: an R package for affinity propagation clustering. Bioinformatics 27, 24632464. DOI: doi:10.1093/bioinformatics/btr406.
See Also
APResult
,
AggExResult
, ExClust
,
heatmapmethods
, apcluster
,
apclusterL
, aggExCluster
,
cutreemethods
Examples
## create two Gaussian clouds
cl1 < cbind(rnorm(50, 0.2, 0.05), rnorm(50, 0.8, 0.06))
cl2 < cbind(rnorm(50, 0.7, 0.08), rnorm(50, 0.3, 0.05))
x < rbind(cl1, cl2)
## run affinity propagation
apres < apcluster(negDistMat(r=2), x, q=0.7, details=TRUE)
## plot information about clustering run
plot(apres)
## plot clustering result
plot(apres, x)
## perform agglomerative clustering of affinity propagation clusters
aggres1 < aggExCluster(x=apres)
## show dendrograms
plot(aggres1)
plot(aggres1, showSamples=TRUE)
## show clustering result for 4 clusters
plot(aggres1, x, k=4)
## perform agglomerative clustering of whole data set
aggres2 < aggExCluster(negDistMat(r=2), x)
## show dendrogram
plot(aggres2)
## show heatmap along with dendrogram
heatmap(aggres2)
## show clustering result for 2 clusters
plot(aggres2, x, k=2)
## cluster iris data set
data(iris)
apIris < apcluster(negDistMat(r=2), iris, q=0)
plot(apIris, iris)