Integer value, how many different directions are
toured.
steps
Integer, number of steps in each direction.
sec
Numerical, lower bound for the number of seconds each
direction takes.
sleep
Numerical, sleep for as many seconds after each picture
has been plotted.
axiscol
If not NULL, then arrows are plotted for
projections of the original coordinate axes in these colors.
axislab
Optional labels for the projected axes.
center
Center of the coordinate system to use in projected
space. Default is the center of the plotting region.
radius
Relative size of the arrows.
minradius
Minimum radius of arrows to include.
asp, ...
Passed on to randomTourMatrix and from there to plot.
Details
Two random locations are chosen, and data then projected onto
hyperplanes which are orthogonal to step vectors interpolating
the two locations. The first two coordinates of the projected data are
plotted. If directions is larger than one, then after the first
steps plots one more random location is chosen, and the
procedure is repeated from the current position to the
new location, etc..
The whole procedure is similar to a grand tour, but no attempt is made
to optimize subsequent directions, randomTour simply chooses a random
direction in each iteration. Use rggobi for the real thing.
Obviously the function needs a reasonably fast computer and graphics
device to give a smooth impression, for x11 it may be
necessary to use type="Xlib" rather than cairo.
Author(s)
Friedrich Leisch
Examples
if(interactive()){
par(ask=FALSE)
randomTour(iris[,1:4], axiscol=2:5)
randomTour(iris[,1:4], col=as.numeric(iris$Species), axiscol=4)
x <- matrix(runif(300), ncol=3)
x <- rbind(x, x+1, x+2)
cl <- cclust(x, k=3, save.data=TRUE)
randomTour(cl, center=0, axiscol="black")
## now use predicted cluster membership for new data as colors
randomTour(cl, center=0, axiscol="black",
data=matrix(rnorm(3000, mean=1, sd=2), ncol=3))
}