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lattice (version 0.10-11)

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,... are optional conditional variables, and
data
optional data frame in which variables are to be evaluated
at
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. The type of labelling can be controlled by the label.style argument, which is passed on to
pretty
logical, whether to use pretty cut locations and 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(), allow.multiple = is.null(groups) || outer, outer = TRUE, aspect = "fill", panel = "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"), ..., default.scales = list(), colorkey = region, col.regions, alpha.regions, subset = TRUE) contourplot(formula, data = parent.frame(), panel = "panel.contourplot", 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).

See Also

xyplot, Lattice, panel.levelplot

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, 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()

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