levelplot {lattice}R Documentation

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 = "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)

## S3 method for class 'formula':
contourplot(x,
             data,
             panel = "panel.contourplot",
             cuts = 7,
             labels = TRUE,
             contour = TRUE,
             pretty = TRUE,
             region = FALSE,
             ...)
## S3 method for class 'matrix':
levelplot(x, data, aspect = "iso", ...)
## S3 method for class 'matrix':
contourplot(x, data, aspect = "iso", ...)


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, g2, ... are optional conditional variables, and must be either factors or shingles if present.
Calculations are based on the assumption that all x and y values are evaluated on a grid (defined by their unique values). The function will not return an error if this is not true, but the display might not be meaningful. However, the x and y values need not be equally spaced.
Both levelplot and wireframe have methods for matrix objects, in which case x provides the z vector described above, while its rows and columns are interpreted as the x and y vectors respectively. This is similar to the form used in filled.contour and image.
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.
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 varying in color (so that nearby colors would be similar). When the colors are actually chosen, they are chosen to be equally spaced along this vector. When there are more regions than col.regions, the colors are recycled.
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:

space:
location of the colorkey, can be one of "left", "right", "top" and "bottom". Defaults to "right".

x, y:
location, currently unused

col:
vector of colors

at:
numeric vector specifying where the colors change. must be of length 1 more than the col vector.

labels:
a character vector for labelling the at values, or more commonly, a list of components labels, at, cex, col, font describing label positions.

tick.number:
approximate number of ticks.

corner:
interacts with x, y; unimplemented

width:
width of the key

height:
length of key w.r.t side of plot.
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 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, default.scales, subset these arguments are described in the help page for xyplot.
... other arguments

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.

Author(s)

Deepayan Sarkar Deepayan.Sarkar@R-project.org

See Also

xyplot, Lattice, panel.levelplot

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()

[Package lattice version 0.14-16 Index]