tileplot {latticeExtra} R Documentation

## Plot a spatial mosaic from irregular 2D points

### Description

Represents 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.

### Usage

```tileplot(x, data = NULL, aspect = "iso",
prepanel = "prepanel.default.xyplot",
panel = "panel.voronoi", ...)
```

### Arguments

 `x, data` formula and data as in `levelplot`, except that it expects irregularly spaced points rather than a regular grid. `aspect` aspect ratio: "iso" is recommended as it reproduces the distances used in the triangulation calculations. `panel, prepanel` see `xyplot`. `...` further arguments to the panel function, which defaults to `panel.voronoi`.

### Details

See `panel.voronoi` for further options and details.

### Author(s)

Felix Andrews felix@nfrac.org

`panel.voronoi`, `levelplot`

### Examples

```xyz <- data.frame(x = rnorm(100), y = rnorm(100), z = rnorm(100))
tileplot(z ~ x * y, xyz)

## tripack is faster but non-free
## Not run:
tileplot(z ~ x * y, xyz, use.tripack = TRUE)

## End(Not run)

## 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)
})
```
[Package latticeExtra version 0.6-25 Index]