randomTour {flexclust} | R Documentation |
Plot a Random Tour
Description
Create a series of projection plots corresponding to a random tour through the data.
Usage
randomTour(object, ...)
## S4 method for signature 'ANY'
randomTour(object, ...)
## S4 method for signature 'matrix'
randomTour(object, ...)
## S4 method for signature 'flexclust'
randomTour(object, data=NULL, col=NULL, ...)
randomTourMatrix(x, directions=10,
steps=100, sec=4, sleep = sec/steps,
axiscol=2, axislab=colnames(x),
center=NULL, radius=1, minradius=0.01, asp=1,
...)
Arguments
object , x |
A matrix or an object of class |
data |
Data to include in plot. |
col |
Plotting colors for data points. |
directions |
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 |
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 |
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))
}