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 class 'data.grid'
image(
  x,
  data.ind = 1,
  xlab = NULL,
  ylab = NULL,
  useRaster = all(dim(x) > dev.size("px")),
  ...
)
# S3 method for class 'data.grid'
persp(x, data.ind = 1, xlab = NULL, ylab = NULL, zlab = NULL, ...)
# S3 method for class 'data.grid'
contour(x, data.ind = 1, filled = FALSE, xlab = NULL, ylab = NULL, ...)a "data.grid"-class object.
integer (or character) with the index (or name) of the component containing the values to be used for coloring the rectangles.
label for the x axis, defaults to dimnames(x)[1].
label for the y axis, defaults to dimnames(x)[2].
logical; if TRUE a bitmap raster is used to plot the
image instead of polygons.
additional graphical parameters (to be passed to main plot function).
label for the z axis, defaults to names(x)[data.ind].
logical; if FALSE (default), function contour
is called, otherwise filled.contour.
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.
# 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)