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voronoiPolygons() is a wrapper function that extracts
the vertices of ‘deldir’ Delaunay triangles and Dirichelet (Voronoi)
tiles for use with functions like graphics::polygon(). The function
returns a list of data frames of vertices. This makes tasks like
coloring tiles or triangles or counting cases within those tiles or
triangles easier.
voronoiPolygons(sites, rw.data = NULL, rw = NULL, type = "tiles")The functions has four arguments. sites is the data
frame of the sites or focal points used to do the tessellation or
triangulation. rw.data (rw = ‘rectangular window’) is the
data frame of a secondary source data (e.g., fatalities, customers,
etc.). This argument is useful when the range of secondary data exceeds
that of the sites data. rw is the deldir way
to specify the range of data. It uses a vector of the corners of the
rectangular window: xmin, xmax, ymin, ymax. type is “tiles”
or “triangles”.
To color tiles and triangles or to count the number of points (e.g.,
fatalities) within each tile or triangle, we can apply
sp::point.in.polygon() to the results of
voronoiPolygons().
# compute vertices of Voronoi tiles
vertices <- voronoiPolygons(sites = cholera::pumps, rw.data = cholera::roads)
# locations of the 578 fatalities in Soho
cases <- cholera::fatalities.unstacked
# count fatalities within each tile
census <- lapply(vertices, function(tile) {
sp::point.in.polygon(cases$x, cases$y, tile$x, tile$y)
})
# ID the 13 water pumps
names(census) <- paste0("p", cholera::pumps$id)
# count of fatalities by neighborhood
vapply(census, sum, integer(1L))
> p1 p2 p3 p4 p5 p6 p7 p8 p9 p10 p11 p12 p13
> 0 1 13 23 6 61 361 16 27 62 2 2 4# compute vertices of Delaunay triangles
vertices <- voronoiPolygons(sites = cholera::pumps,
rw.data = cholera::roads, type = "triangles")
# locations of the 578 fatalities in Soho
cases <- cholera::fatalities.unstacked
# count fatalities within each triangle
census <- lapply(vertices, function(tile) {
sp::point.in.polygon(cases$x, cases$y, tile$x, tile$y)
})
# ID triangles
names(census) <- paste0("t", seq_along(vertices))
# count of fatalities by triangle
vapply(census, sum, integer(1L))
> t1 t2 t3 t4 t5 t6 t7 t8 t9 t10 t11 t12 t13 t14 t15 t16 t17
> 1 0 1 11 43 179 35 2 18 138 15 22 97 0 0 4 1# compute vertices of Voronoi tiles
vertices <- voronoiPolygons(sites = cholera::pumps, rw.data = cholera::roads)
# define colors
snow.colors <- grDevices::adjustcolor(snowColors(), alpha.f = 1/3)
# plot map and color coded tiles
snowMap(add.cases = FALSE)
invisible(lapply(seq_along(vertices), function(i) {
polygon(vertices[[i]], col = snow.colors[[i]])
}))
# compute vertices of Delaunay triangles
vertices <- voronoiPolygons(sites = cholera::pumps,
rw.data = cholera::roads, type = "triangles")
# define colors
colors.pair <- RColorBrewer::brewer.pal(10, "Paired")
colors.dark <- RColorBrewer::brewer.pal(8, "Dark2")
brewer.colors <- sample(c(colors.pair, colors.dark))
colors <- grDevices::adjustcolor(brewer.colors, alpha.f = 1/3)
# plot map and color coded triangles
snowMap(add.cases = FALSE)
invisible(lapply(seq_along(vertices), function(i) {
polygon(vertices[[i]], col = colors[[i]])
}))
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They may not be fully stable and should be used with caution. We make no claims about them.
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