lattice (version 0.17-12)

levelplot: Level Plots

Description

Draw Level Plots and Contour plots.

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)

Arguments

x
for the formula method, 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,
data
For the formula methods, an optional data frame in which variables in the formula (as well as groups and subset, if any) are to be evaluated. Usually ignored with a warning in other cases.
row.values, column.values
Optional vectors of values that define the grid when x is a matrix. row.values and column.values must have the same lengths as nrow(x) and ncol(x) respectively. By default, row
panel
panel function used to create the display, as described in xyplot
aspect
For the matrix methods, the default aspect ratio is chosen to make each cell square. The usual default is aspect="fill", as described in xyplot.
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
alpha.regions
numeric, specifying alpha transparency (works only on some devices)
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:

[object Object],[object Object],[object Object],[object Object],[object Object],[obje

contour
logical, whether to draw contour lines.
cuts
number of levels the range of z would be divided into
labels
typically a logical indicating whether contour lines should be labelled, but other possibilities for more sophisticated control exists. Details are documented in the help page for panel.levelplot<
pretty
logical, whether to use pretty cut locations and labels
region
logical, whether regions between contour lines should be filled
allow.multiple, outer, prepanel, scales, strip, groups, xlab, xlim, ylab, ylim, drop.unused.levels, lattice.options, default.scales, subset
these arguments are described in the help page for xyplot.
...
other arguments. Some are processed by levelplot or contourplot, and those unrecognized are passed on to the panel function.

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.

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).

References

Sarkar, Deepayan (2008) "Lattice: Multivariate Data Visualization with R", Springer. http://lmdvr.r-forge.r-project.org/

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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