[R] Distances between two datasets of x and y co-ordinates

[Liaw, Andy]

From: adrian at maths.uwa.edu.au
 
> Andrew McFadden <Andrew.McFadden at maf.govt.nz> writes:
> 
> > I am trying to determine the distances between two datasets 
> of x and y
> > points.
> 
> This can be done efficiently in the package 'spatstat'.
> 
>      library(spatstat)
>      crossdist(x1, y1, x2, y2)
> 
> where x1, y1 are vectors of coordinates for the first set of points
> and x2, y2 for the second set. See help(crossdist.default)
> 
> This is executed in C and is faster than using outer() or apply().

The margin may not be as large as you imagine:

crossdist2 <- function(x1, y1, x2, y2) {
    c1 <- complex(real=x1, imaginary=y1)
    c2 <- complex(real=x2, imaginary=y2)
    dist <- outer(c1, c2, function(z1, z2) Mod(z1-z2))
    dist
}

R> set.seed(17)
R> n <- 1000
R> x1 <- rnorm(n)
R> y1 <- rnorm(n)
R> x2 <- rnorm(n)
R> y2 <- rnorm(n)
R> system.time(d2 <- crossdist2(x1, y1, x2, y2))
   user  system elapsed 
   1.03    0.09    1.17 
R> library(spatstat)
R> system.time(d1 <- crossdist2(x1, y1, x2, y2))
   user  system elapsed 
   1.08    0.03    1.12 
R> all.equal(d1, d2)
[1] TRUE

Andy


 
> The result is a matrix giving the distance between each pair of points
> (the first point in the first dataset and the second point in 
> the second
> set). If these datasets are large, you can of course run into 
> trouble with
> the size of this matrix.
> 
> If you just wanted to find the distance to the *nearest* point
> (or identify which point is nearest), use the function nncross().
> 
> Adrian Baddeley
> 
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> 
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