| clmplot {cba} | R Documentation |
A wrapper function to image that produces a level plot with the option to color the rows (or columns) based on a clustering and/or classification of the data, and the option to reorder the rows and columns for better presentation.
clmplot(x, col, col.bycol = FALSE, order=FALSE, dists.method = "binary",
hclust.method = "average", axes = FALSE, xlab = "", ylab = "", ...)
x |
an logical matrix. |
col |
an optional vector defining a coloring. |
col.bycol |
option to color by columns. |
order |
option to (pre)order the rows and columns. |
dists.method |
method to be used by dists. |
hclust.method |
method to be used by hclust. |
axes |
option to plot axes. |
xlab, ylab |
labels for the x and y axis. |
... |
further arguments to image. |
For dummy coded data the level FALSE is assumed to carry no
information and is colored "white". Thus, the level TRUE can
be colored according to some classification of the rows (or columns)
of the data matrix. If no color specification is supplied the default
color black is used.
If col is of type character it is assumed to contain color codes.
Otherwise, it must be a factor and the levels are assigned colors
from heat.colors.
If order is TRUE the rows and columns are ordered
by hclust where the distances are computed by dists.
Note that an axis is only plotted if the number of elements (rows or columns) is less than 100.
A list with the following components:
rows |
the row order. |
cols |
the column order. |
Christian Buchta
lmplot for plotting of logical data at reduced resolutions,
heatmap for ordered plotting of real-valued data, and
package gclus for ordering functions.
x <- matrix(sample(c(FALSE,TRUE),100,rep=TRUE),ncol=10)
clmplot(x, order=TRUE, axes=TRUE)
clmplot(x, col=rep(c(1,2),each=5))
clmplot(x, col=rep(c("red","blue"),each=5))
clmplot(x, col=rep(c("red","blue"),each=5), col.bycol=TRUE)
## Not run:
### continue example (see rockCluster)
col <- Votes$Class # color by party
levels(col) <- c("red","blue")
op <- par(mfrow=c(1,2), pty="s")
clmplot(x, order=TRUE, col=as.character(col), main="Parties")
col <- rf$cl # color by cluster
levels(col) <- c("blue","red","green", "black") # map NA to black
clmplot(x, order=TRUE, col=as.character(col), main="Clusters")
par(op)
## End(Not run)