Best way to plot cross sections of discrete-valued grids

I have a 3-D grid where the values of the cells are a small number of
discrete values.  (The grid represents subsurface soil and geology
types.)  Contiguous regions of the same value are relatively few in
number and large in size in comparison to the whole domain.  I am
looking for advice on two things:

1)  What is the best way to sample the grid along any transect defined
by a line between (x1, y1) and (x2, y2), and plot the 2-D vertical cross
section?  I would like to sample not only in the orthogonal directions
defined by the grid but along any other compass bearing as well.
Lattice plotting capability is desired.

At first I thought the best thing to do here would be to use 
contourLines to get the contiguous region boundaries and then work out 
all the intersections of the contour lines with your transect from x1,y1 
to x2,y2. But... You've got categorical data, so the contour function, 
which only works with numerical data, might get messed up...

  So I can only think that you will have to walk along the transect with 
a small step size (1/4 grid size will only miss a few corners), sampling 
from your grid as you go, ending up with a vector of coordinates and 
grid samples.

  Code to do this is fairly straightforward, depending on how complex 
your grids are - evenly spaced, defined by edges or centres, similar in 
X and Y etc etc.

vo=list(x=1:87,y=1:61,z=volcano)
   image(vo)
   t1=transectGrid(locator(1,type='p'),locator(1,type='p'),vo)
   plot(t1[,1],t1[,3],type='l')

Just click twice. Three short R functions are attached. Hopefully thats 
the sort of thing you are looking for!

Barry


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