# -- Open a graphical display window.
plot.window()

# -- Create the plot base, but without the points yet (type="n").  We will add 
# -- the points next.  I used xlim and ylim to make a slightly nicer looking 
# -- plot, but this is not necessary.  

a <- 0.25	# -- change this value to zoom in and out.
		# -- Close-up (and contour) uses a = 0.25.
		# -- Zoomed-out uses a = 10.

# -- Plot window range.
rx <- c( min( ozone$lon.lat[,1]) - a, max( ozone$lon.lat[,1]) + a)
ry <- c( min( ozone$lon.lat[,2]) - a, max( ozone$lon.lat[,2]) + a)

plot(	ozone$lon.lat[,1],
	ozone$lon.lat[,2],
	type="n",
	xlim=rx,
	ylim=ry,
	xlab="East-West",
	ylab="North-South")


# -- Optional colorization of plot.
# -- Create vector to colorize plot by levels of ozone in the atmosphere.
ocol <- c(2, 1, 1, 1, 3, 4, 3, 3, 6, 3, 5, 4, 5, 4, 5, 6, 2, 7, 5, 7)

# -- Now we will plot the points using the actual ozone concentrations on the 
# -- plot at the corresponding lon and lat.  I have also added color strictly
# -- for appearances (col=ocol).

text(	ozone$lon.lat[,1],
        ozone$lon.lat[,2],
	labels=ozone$y,
	col=ocol)

# -- superimpose a map of the region onto the plot.  

usa( add=T, xlim = rx, ylim = ry, lty=2)

title("Ozone Concentrations in the Midwestern U.S.")

# -- The Contour Plot.  Use same steps as above, but add contour lines.
intrp <- interp( ozone$lon.lat[,1], ozone$lon.lat[,2], ozone$y)
contour( intrp, add=T, labex=0)

# -- To plot the standard errors of the krig fit with contours.  Do same as
# -- above, except use the se object (ozone.fit.se) instead of ozone$y

# -- Surface Plot.  (ozone.fit is Krig object)
look<- predict.surface( ozone.fit) 
image.plot( look, graphics.reset=F)
look2<- predict.surface.se( ozone.fit)
contour( look2, add=T)
title("Ozone Data Example: Surface Plot w/ Standard Error Contour Lines")