lattice (version 0.17-10)

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)

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

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()