levelplot
Level Plots
Draw Level Plots and Contour plots.
- Keywords
- hplot
Usage
levelplot(x, data, ...)
contourplot(x, data, ...)## S3 method for class 'formula':
levelplot(x,
data,
allow.multiple = is.null(groups) || outer,
outer = TRUE,
aspect = "fill",
panel = lattice.getOption("panel.levelplot"),
prepanel = NULL,
scales = list(),
strip = TRUE,
groups = NULL,
xlab,
xlim,
ylab,
ylim,
at,
cuts = 15,
pretty = FALSE,
region = TRUE,
drop.unused.levels = lattice.getOption("drop.unused.levels"),
...,
lattice.options = NULL,
default.scales = list(),
colorkey = region,
col.regions,
alpha.regions,
subset = TRUE)
## S3 method for class 'formula':
contourplot(x,
data,
panel = lattice.getOption("panel.contourplot"),
cuts = 7,
labels = TRUE,
contour = TRUE,
pretty = TRUE,
region = FALSE,
...)
## S3 method for class 'matrix':
levelplot(x, data = NULL, aspect = "iso", \dots,
xlim, ylim, row.values, column.values)
## S3 method for class 'matrix':
contourplot(x, data = NULL, aspect = "iso", \dots,
xlim, ylim, row.values, column.values)
Details
These and all other high level Trellis functions have several
arguments in common. These are extensively documented only in the
help page for 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).
Value
An object of class "trellis"
. The
update
method can be used to
update components of the object and the
print
method (usually called by
default) will plot it on an appropriate plotting device.
References
Sarkar, Deepayan (2008) "Lattice: Multivariate Data Visualization with
R", Springer.
See Also
Examples
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()