Nearest Neighbour Index Map as a Function

Compute the nearest neighbour index map of an object, and return it as a function.

spatial, math
nnfun(X, ...)

# S3 method for ppp nnfun(X, ..., k=1, value=c("index", "mark"))

# S3 method for psp nnfun(X, ..., value=c("index", "mark"))


Any suitable dataset representing a two-dimensional collection of objects, such as a point pattern (object of class "ppp") or a line segment pattern (object of class "psp").


A single integer. The kth nearest neighbour will be found.

Extra arguments are ignored.


String (partially matched) specifying whether to return the index of the neighbour (value="index", the default) or the mark value of the neighbour (value="mark").


For a collection \(X\) of two dimensional objects (such as a point pattern or a line segment pattern), the “nearest neighbour index function” of \(X\) is the mathematical function \(f\) such that, for any two-dimensional spatial location \((x,y)\), the function value f(x,y) is the index \(i\) identifying the closest member of \(X\). That is, if \(i = f(x,y)\) then \(X[i]\) is the closest member of the collection \(X\) to the location \((x,y)\).

The command f <- nnfun(X) returns a function in the R language, with arguments x,y, that represents the nearest neighbour index function of X. Evaluating the function f in the form v <- f(x,y), where x and y are any numeric vectors of equal length containing coordinates of spatial locations, yields the indices of the nearest neighbours to these locations.

If the argument k is specified then the k-th nearest neighbour will be found.

The result of f <- nnfun(X) also belongs to the class "funxy" and to the special class "nnfun". It can be printed and plotted immediately as shown in the Examples.

A nnfun object can be converted to a pixel image using as.im.


A function with arguments x,y. The function also belongs to the class "nnfun" which has a method for print. It also belongs to the class "funxy" which has methods for plot, contour and persp.

See Also

distfun, plot.funxy

  • nnfun
  • nnfun.ppp
  • nnfun.psp
   f <- nnfun(cells)
   f(0.2, 0.3)

   g <- nnfun(cells, k=2)
   g(0.2, 0.3)

   plot(nnfun(amacrine, value="m"))

   L <- psp(runif(10), runif(10), runif(10), runif(10), window=owin())
   h <- nnfun(L)
   h(0.2, 0.3)
# }
Documentation reproduced from package spatstat, version 1.63-0, License: GPL (>= 2)

Community examples

Looks like there are no examples yet.