tileplot.RdRepresents an irregular set of (x, y) points with a color covariate. Polygons are drawn enclosing the area closest to each point. This is known variously as a Voronoi mosaic, a Dirichlet tesselation, or Thiessen polygons.
tileplot(x, data = NULL, aspect = "iso",
prepanel = "prepanel.default.xyplot",
panel = "panel.voronoi", ...)formula and data as in
levelplot, except that it expects irregularly
spaced points rather than a regular grid.
aspect ratio: "iso" is recommended as it reproduces the distances used in the triangulation calculations.
see xyplot.
further arguments to the panel function, which defaults to
panel.voronoi.
See panel.voronoi for further options and details.
xyz <- data.frame(x = rnorm(100), y = rnorm(100), z = rnorm(100))
tileplot(z ~ x * y, xyz)
## Alternative backend using 'deldir' package
if (FALSE) { # \dontrun{
tileplot(z ~ x * y, xyz, backend = "deldir")
} # }
## showing rectangular window boundary
tileplot(z ~ x * y, xyz, xlim = c(-2, 4), ylim = c(-2, 4))
## insert some missing values
xyz$z[1:10] <- NA
## the default na.rm = FALSE shows missing polygons
tileplot(z ~ x * y, xyz, border = "black",
col.regions = grey.colors(100),
pch = ifelse(is.na(xyz$z), 4, 21),
panel = function(...) {
panel.fill("hotpink")
panel.voronoi(...)
})
## use na.rm = TRUE to ignore points with missing values
update(trellis.last.object(), na.rm = TRUE)
## a quick and dirty approximation to US state boundaries
tmp <- state.center
tmp$Income <- state.x77[,"Income"]
tileplot(Income ~ x * y, tmp, border = "black",
panel = function(x, y, ...) {
panel.voronoi(x, y, ..., points = FALSE)
panel.text(x, y, state.abb, cex = 0.6)
})