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Voronoi mosaic

voronoi.mosaic.Rd

This function creates a Voronoi mosaic out of a given set of arbitraryly located points in the plane. Each cell of a voronoi mosaic is associated with a data point and contains all points \((x,y)\) closest to this data point.

Usage

voronoi.mosaic(x, y = NULL, duplicate = "error")

Arguments

x

vector containing \(x\) coordinates of the data. If y is missing x should be a list or dataframe with two components x and y.

x can also be an object of class triSht generated by tri.mesh. In this case the internal triangulation step can be skipped.

y

vector containing \(y\) coordinates of the data. Can be omitted if x is a list with two components x and y.

duplicate

flag indicating how to handle duplicate elements. Possible values are:

  • "error" – default,

  • "strip" – remove all duplicate points,

  • "remove" – leave one point of the duplicate points.

Details

The function creates first a Delaunay triangulation (if not already given), extracts the circumcircle centers of these triangles, and then connects these points according to the neighbourhood relations between the triangles.

Value

An object of class voronoi.

References

G. Voronoi, Nouvelles applications des parametres continus a la theorie des formes quadratiques. Deuxieme memoire. Recherches sur les parallelloedres primitifs, Journal fuer die reine und angewandte Mathematik, 1908, vol 134, p. 198-287

Author

Albrecht Gebhardt <[email protected]>, Roger Bivand <[email protected]>

Note

This function is meant as a replacement for function voronoi.mosaic from package tripack. Please note that the underlying triangulation uses a different algorithm, see tri.mesh. Contrary to tri.mesh this should not affect the result for non unique triangulations e.g. on regular grids as the voronoi mosaic in this case will still be unique.

The arguments are backward compatible, even the returned object should be compatible with functions from package tripack.

See also

voronoi,voronoi.mosaic, print.voronoi, plot.voronoi

Examples

data(franke)
fd <- franke$ds3
vr <- voronoi.mosaic(fd$x, fd$y)
summary(vr)
#> voronoi mosaic
#> Call: voronoi.mosaic(x = fd$x, y = fd$y) 
#> 40 nodes
#> 8 dummy nodes