R Graphics for gridded data

Draw an image, perspective, contour or filled contour plot for data on a bidimensional regular grid (S3 methods for class "data.grid").

# S3 method for data.grid
image(x, data.ind = 1, xlab = NULL, ylab = NULL, ...)

# S3 method for data.grid
persp(x, data.ind = 1, xlab = NULL, ylab = NULL, zlab = NULL, ...)

# S3 method for data.grid
contour(x, data.ind = 1, filled = FALSE, xlab = NULL, ylab = NULL, ...)

Arguments

x

a "data.grid"-class object.

data.ind

integer (or character) with the index (or name) of the component containing the values to be used for coloring the rectangles.

xlab

label for the x axis, defaults to dimnames(x)[1].

ylab

label for the y axis, defaults to dimnames(x)[2].

...

additional graphical parameters (to be passed to main plot function).

zlab

label for the z axis, defaults to names(x)[data.ind].

filled

logical; if FALSE (default), function contour is called, otherwise filled.contour.

Value

image() and contour() do not return any value, call for secondary effects (generate the corresponding plot). persp() invisibly returns the viewing transformation matrix (see persp for details), a 4 x 4 matrix that can be used to superimpose additional graphical elements using the function trans3d.

See also

image, persp, contour, filled.contour, data.grid.

Examples

# Regularly spaced 2D data
grid <- grid.par(n = c(50, 50), min = c(-1, -1), max = c(1, 1))
f2d <- function(x) x[1]^2 - x[2]^2
trend <- apply(coords(grid), 1, f2d)
set.seed(1)
y <- trend + rnorm(prod(dim(grid)), 0, 0.1)
gdata <- data.grid(trend = trend, y = y, grid = grid)
# perspective plot
persp(gdata, main = 'Trend', theta = 40, phi = 20, ticktype = "detailed")

# filled contour plot
contour(gdata, main = 'Trend', filled = TRUE, color.palette = jet.colors)

# Multiple plots with a common legend:
scale.range <- c(-1.2, 1.2)
scale.color <- jet.colors(64)
# 1x2 plot with some room for the legend...
old.par <- par(mfrow = c(1,2), omd = c(0.05, 0.85, 0.05, 0.95))
image(gdata, zlim = scale.range, main = 'Trend', col = scale.color)
contour(gdata, add = TRUE)
image(gdata, 'y', zlim = scale.range, main = 'Data', col = scale.color)
contour(gdata, 'y', add = TRUE)
par(old.par)
# the legend can be added to any plot...
splot(slim = scale.range, col = scale.color, add = TRUE)