nnfun

Nearest Neighbour Index Map as a Function

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

Usage

nnfun(X, ...)
  ## S3 method for class 'ppp':
nnfun(X, ..., k=1)
  ## S3 method for class 'psp':
nnfun(X, ...)

Details

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 Rlanguage, 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.

See Also

distfun, plot.funxy

Aliases

• nnfun
• nnfun.ppp
• nnfun.psp

Examples

f <- nnfun(cells)
   f
   plot(f)
   f(0.2, 0.3)

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

   L <- psp(runif(10), runif(10), runif(10), runif(10), window=owin())
   h <- nnfun(L)
   h(0.2, 0.3)