cccmap {iL04}R Documentation

Plot a stochastic clustering on a topographic map

Description

Repeated stochastic clustering, followed by multidimensional scaling into three dimensions is interpreted as a set of red, green, and blue values, and used to plot a coloured topographic cluster map.

Usage

cccmap(coo, dst, n = 50, noise = .5, labels = "dots", cex = 1, seq = 25:1, bwlim = .55, map = NULL,
       xlab = NULL, ylab = NULL, eqrgb = TRUE, ...)

Arguments

coo a dataframe with x- and y-coordinates of locations stored in the first two columns, and names of locations stored as rownames.
dst a dissimilarity structure as produced by the dist function, with names stored in the attribute "Labels".
n number of runs.
noise noise level.
labels what to use as labels. This is either a word: one of "none" (no labels), "names" (use rownames of argument coo), or "dots" (use dots); or a vector of labels ordered in accordance with the data in argument coo.
cex the size of the labels relative to the default text size.
seq a sequence of decreasing sizes of the area to fill around each location, relative to the default text size.
bwlim a value between 0 and 1, determining the point to switch between white labels and black labels, relative to the background colour interpreted as a grey value between 0 and 1.
map an optional two-column matrix with a set of line segments, used to draw a map. See lines for the use of NA values.
xlab a title for the x axis.
ylab a title for the y axis.
eqrgb equal scaling of rgb values.
... further arguments to the plot function.

Value

None.

References

RuG/L04 - software for dialectometrics and cartography: http://www.let.rug.nl/~kleiweg/L04/

See Also

clustermap, linkmap, mdsmap, mean.asp

Examples

data(PA)
data(PA.coo)
data(PA.map)
asp <- mean.asp(PA.map[, 2])
cccmap(PA.coo[, 1:2], PA, labels = PA.coo$idx,
       main = "Pennsylvania, USA",
       asp = asp, map = PA.map)

[Package iL04 version 1.15 Index]