levelplot: Level Plots

Description

Draw Level Plots and Contour plots.

Usage

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,
            ...)

Arguments

formula

a formula of the form z ~ x * y | g1 * g2 * ..., where z is a numeric response, and x, y are numeric values evaluated on a rectangular grid. g1,g2,..., if present, must be either factor

data

optional data frame in which variables are to be evaluated

numeric vector giving breaks along the range of z. Contours (if any) will be drawn at these heights, and the regions in between would be colored using col.regions.

col.regions

color vector to be used if regions is TRUE. The general idea is that this should be a color vector of moderately large length (longer than the number of regions. By default this is 100). It is expected that this vector would be gradually varyi

colorkey

logical specifying whether a color key is to be drawn alongside the plot, or a list describing the color key. The list may contain the following components:

space location of the colorkey, can be one of ``left'', ``right'', `

contour

logical, whether to draw contour lines.

cuts

number of levels the range of z would be divided into

labels

logical specifying whether contour lines should be labelled, or character vector of labels for contour lines. This is not well-implemented yet, don't count on it. The type of labelling can be controlled by the label.style argument

pretty

logical, whether to use pretty labels

region

logical, whether regions between contour lines should be filled

...

other arguments

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.

synopsis

levelplot(formula, data = parent.frame(), aspect = "fill", layout = NULL, panel = "panel.levelplot", prepanel = NULL, scales = list(), strip = TRUE, groups = NULL, xlab, xlim, ylab, ylim, at, contour = FALSE, cuts = 15, labels = FALSE, pretty = FALSE, region = TRUE, ..., colorkey = region, col.regions = trellis.par.get("regions")$col, subscripts = TRUE, subset = TRUE) contourplot(formula, data = parent.frame(), panel = "panel.levelplot", prepanel = NULL, strip = TRUE, groups = NULL, cuts = 7, labels = TRUE, contour = TRUE, pretty = TRUE, region = FALSE, ..., subset = TRUE)

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).

Examples

Run this code

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$z <- cos(r^2) * exp(-r/(pi^3))
levelplot(z~x*y, grid, cuts = 50, xlab="", ylab="",
          main="Weird Function", colorkey = FALSE)
levelplot(z~x*y, grid, cuts = 50, scales=list(log="e"), xlab="",
          ylab="", main="Weird Function", sub="with log scales",
          colorkey = FALSE, region = TRUE)
#S+ example
library(modreg)
data(environmental)
attach(environmental)
ozo.m <- loess((ozone^(1/3)) ~ wind * temperature * radiation,
       parametric = c("radiation", "wind"), span = 1, degree = 2)
w.marginal <- seq(min(wind), max(wind), length = 50)
t.marginal <- seq(min(temperature), max(temperature), length = 50)
r.marginal <- seq(min(radiation), max(radiation), length = 4)
wtr.marginal <- list(wind = w.marginal, temperature = t.marginal,
        radiation = r.marginal)
grid <- expand.grid(wtr.marginal)
grid[, "fit"] <- c(predict(ozo.m, grid))
contourplot(fit ~ wind * temperature | radiation, data = grid,
          cuts = 10, region = TRUE,
          xlab = "Wind Speed (mph)",
          ylab = "Temperature (F)",
          main = "Cube Root Ozone (cube root ppb)",
          col.regions = trellis.par.get("regions")$col)
detach()

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