Distance Map as a Function
Compute the distance function of an object, and return it as a function.
distfun(X, ...) ## S3 method for class 'ppp' distfun(X, ..., k=1, undef=Inf) ## S3 method for class 'psp' distfun(X, ...) ## S3 method for class 'owin' distfun(X, ..., invert=FALSE)
X |
Any suitable dataset representing a two-dimensional
object, such as a point pattern (object of class |
... |
Extra arguments are ignored. |
k |
An integer. The distance to the |
undef |
The value that should be returned if the distance is undefined
(that is, if |
invert |
If |
The “distance function” of a set of points A is the
mathematical function f such that, for any
two-dimensional spatial location (x,y),
the function value f(x,y)
is the shortest distance from (x,y) to A.
The command f <- distfun(X) returns a function
in the R language, with arguments x,y, that represents the
distance 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 values of the distance function at these
locations. Alternatively x can be a
point pattern (object of class "ppp" or "lpp") of
locations at which the distance function should be computed (and then
y should be missing).
This should be contrasted with the related command distmap
which computes the distance function of X
on a grid of locations, and returns the distance
values in the form of a pixel image.
The result of f <- distfun(X) also belongs to the class
"funxy" and to the special class "distfun".
It can be printed and plotted immediately as shown in the Examples.
A distfun object can be converted to a pixel image
using as.im.
A function with arguments x,y.
The function belongs to the class "distfun" which has
methods for print and summary, and for geometric
operations like shift.
It also belongs to the class "funxy" which has methods
for plot, contour and persp.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk.
f <- distfun(letterR) f plot(f) f(0.2, 0.3) plot(distfun(letterR, invert=TRUE), eps=0.1) d <- distfun(cells) d2 <- distfun(cells, k=2) d(0.5, 0.5) d2(0.5, 0.5) domain(d) summary(d) z <- d(japanesepines)
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