levelplot(formula, data,
at,
contour = FALSE,
cuts = 15,
pretty = FALSE,
region = TRUE,
...,
col.regions = trellis.par.get("regions")$col,
colorkey = region)
contourplot(formula, data, at,
contour = TRUE,
labels = format(at),
cuts = 7,
pretty = TRUE,
...)
z ~ x * y | g1 * g2 * ...
,
where z
is a numeric response, and x, y
are numeric
values evaluated on a rectangular grid. g1,g2,...
are
optional conditional variables, andz
. Contours
(if any) will be drawn at these heights, and the regions in between
would be colored using col.regions
. space
location of the colorkey, can be one of ``left'',
``right'', `
z
would be divided intolabel.style
argument, which is
passed on to
xyplot
, which should be consulted to learn more
detailed usage. Other useful arguments are mentioned in the help page for the default
panel function panel.levelplot
(these are formally
arguments to the panel function, but can be specified in the high
level calls directly).
xyplot
, Lattice
,
panel.levelplot
x <- seq(pi/4, 5 * pi, length = 100)
y <- seq(pi/4, 5 * pi, length = 100)
r <- as.vector(sqrt(outer(x^2, y^2, "+")))
grid <- expand.grid(x=x, y=y)
grid$z <- cos(r^2) * exp(-r/(pi^3))
levelplot(z~x*y, grid, cuts = 50, scales=list(log="e"), xlab="",
ylab="", main="Weird Function", sub="with log scales",
colorkey = FALSE, region = TRUE)
#S-PLUS example
require(stats)
attach(environmental)
ozo.m <- loess((ozone^(1/3)) ~ wind * temperature * radiation,
parametric = c("radiation", "wind"), span = 1, degree = 2)
w.marginal <- seq(min(wind), max(wind), length = 50)
t.marginal <- seq(min(temperature), max(temperature), length = 50)
r.marginal <- seq(min(radiation), max(radiation), length = 4)
wtr.marginal <- list(wind = w.marginal, temperature = t.marginal,
radiation = r.marginal)
grid <- expand.grid(wtr.marginal)
grid[, "fit"] <- c(predict(ozo.m, grid))
contourplot(fit ~ wind * temperature | radiation, data = grid,
cuts = 10, region = TRUE,
xlab = "Wind Speed (mph)",
ylab = "Temperature (F)",
main = "Cube Root Ozone (cube root ppb)")
detach()
Run the code above in your browser using DataLab