Filled vector contours

On 2014-08-24 Jan Tosovsky wrote:

On 2014-08-24 Prof Brian Ripley wrote:

On 24/08/2014 08:51, Jan Tosovsky wrote:

I am trying to create vector output (SVG) of filled contours.

I've found two approaches so far:

(1)
library('lattice')
svg("D:/test.svg")
filled.contour(volcano)
#levelplot(volcano, panel=panel.levelplot.raster)
dev.off()

(2)
library("raster")
svg("D:/test.svg")
rr <- raster(t(volcano))
rc <- cut(rr, breaks= 10)
pols <- rasterToPolygons(rc, dissolve=T)
spplot(pols)
dev.off()

But I'd like to get smooth closed polygons not broken into small
cells.

But the region between two contours is not in general a closed
polygon.

I appologize for not being precise here.

My goal is to get something like this:
http://drifted.in/other/contours/composition.svg

which is a composition of level plots, e.g.
http://drifted.in/other/contours/level_plot.svg

By 'level plot' I mean the cut of the data at certain level. It is
always a closed polygon (or multiple polygons) consisting of contour 
lines connected, if required, by border lines.

For me it is preferred way over 'isoband', which doesn't include areas
hidden by upper levels:
http://drifted.in/other/contours/isoband.svg

Most people with any R experience would have thought that "levelplot"
referred to something like:
(Example 6.9 from Lattice, by Deepayan Sarkar to which I have only
added the contour line parameter which it appears is what you were 
seeking.)

library("locfit") ; library(lattice)
env <- environmental
env$ozone <- env$ozone^(1/3)
env$Radiation <- equal.count(env$radiation, 4)
fm1.env <- lm(ozone ~ radiation * temperature * wind, env)
fm2.env <- loess(ozone ~ wind * temperature * radiation, env, span =
0.75, degree = 1)
fm3.env <- loess(ozone ~ wind * temperature * radiation, env,
parametric
= c("radiation", "wind"), span = 0.75, degree = 2)

fm4.env <- locfit(ozone ~ wind * temperature * radiation, env)

w.mesh <- with(env, do.breaks(range(wind), 50))
t.mesh <- with(env, do.breaks(range(temperature), 50))
r.mesh <- with(env, do.breaks(range(radiation), 3))
grid <- expand.grid(wind = w.mesh, temperature = t.mesh, radiation =
r.mesh)
grid[["fit.linear"]] <- predict(fm1.env, newdata = grid)
grid[["fit.loess.1"]] <- as.vector(predict(fm2.env, newdata = grid))
grid[["fit.loess.2"]] <- as.vector(predict(fm3.env, newdata = grid))
grid[["fit.locfit"]] <- predict(fm4.env, newdata = grid)

png()
print(levelplot(fit.linear + fit.loess.1 + fit.loess.2 + fit.locfit ~
wind * temperature | radiation, data = grid, contour=TRUE))
dev.off()