oldPicketplot: Barplots for Several Binary Variables
In Heatplus: Heatmaps with row and/or column covariates and colored clusters

Description Usage Arguments Details Note Author(s) See Also Examples

Display one or more binary variables by using black bars for presence/validity of a condition, empty space for absence/invalidity, and an extra color for missing values. Additionally, an index plot for one interval scaled variable can be added, possibly with a smoothing function (OLD version, to be deprecated).

This routine is primarily intended for augmenting heatmaps. It might be useful in other contexts, but misses most frills for using it comfortably.

1 2	oldPicketplot(x, covariate = NULL, grp = NULL, grpcol, grplabel = NULL, add = FALSE, control = list())

`x`	a matrix or data frame containing the data.
`covariate`	the index of the column in `x` that contains the interval scaled variable, if any.
`grp`	cluster indices for the rows of `x`, used for assigning background color.
`grpcol`	colors corresponding to the clusters.
`grplabel`	cluster names.
`add`	logical indicating whether to start a new plot, or whether to add the plot to the existing one.
`control`	a list of parameters controlling the appearance of the plot, see Details.

The following named list elements can be set to change the appearance of the plot:

boxw: the relative width of a marking box.
boxh: the relative height of a marking box.
hbuff: the horizontal separation around marking boxes; equals half the horizontal distance between two marking boxes.
vbuff: ditto for vertical separation.
span: passed on to loess used for the smoothing curve.
nacol: color for missing values of binary variables.
degree: if 0, no smoothing line is drawn; otherwise passed on to loess used for the smoothing curve.
cex.label: the character size for grplabel.

The plot looks like a more or less derelict picket fence, and 'picketplot' sounds somewhat like the 'pocketplot' used in geostatistics.

Alexander Ploner <Alexander.Ploner@ki.se>

heatmap_plus

# without covariate
mm = cbind(sample(0:1, 42, rep=TRUE), sample(0:1, 42, rep=TRUE))
mm[sample(42, 5), 1] = NA
oldPicketplot(mm)

# with clustering
cl = rep(1:3, c(10,22,10))
cn = c("Cluster I","Cluster II","Cluster III")
cc = c("lightblue","lightgreen","lightpink") # windows palette
oldPicketplot(mm, grp=cl, grplabel=cn, grpcol=cc)

# add a covariate; setting the colnames makes the variable labels
mm = cbind(mm, rnorm(42) + cl/2)
colnames(mm) = c("State A","State B", "X")
oldPicketplot(mm, covariate=3,grp=cl, grplabel=cn, grpcol=cc)

# using extra controls
oldPicketplot(mm, covariate=3,grp=cl, grplabel=cn, grpcol=cc, control=list(nacol="white", degree=0))