2D density tophat

In case anyone other than me was interested, a pretty efficient  
circular tophat can be made using the fields function fields.rdist.near:

CircHat=function (x, y, h=1, gridres = c((max(x)-min(x))/25,(max(y)- 
min(y))/25), lims = c(range(x), range(y)),density=FALSE)
{
	require(fields)
     nx <- length(x)
     ny <- length(y)
     n=c(1+(lims[2]-lims[1])/gridres[1],1+(lims[4]-lims[3])/gridres[2])
     if (length(y) != nx)
         stop("data vectors must be the same length")
     if (any(!is.finite(x)) || any(!is.finite(y)))
         stop("missing or infinite values in the data are not allowed")
     if (any(!is.finite(lims)))
         stop("only finite values are allowed in 'lims'")
     gx <- seq(lims[1], lims[2], by = gridres[1])
     gy <- seq(lims[3], lims[4], by = gridres[2])
     fullgrid=expand.grid(gx,gy)

     if (missing(h))
         h <- c(bandwidth.nrd(x), bandwidth.nrd(y))
     
temp 
= 
table 
(fields 
.rdist 
.near 
(as 
.matrix 
(fullgrid 
),as.matrix(cbind(x,y)),mean.neighbor=ceiling(length(x)*pi*h^2/ 
((lims[2]-lims[1])*(lims[4]-lims[3]))),delta=h)$ind[,1])
     	
pad=rep(0,length(gx)*length(gy))
pad[as.numeric(names(temp))]=as.numeric(temp)

z <- matrix(pad, length(gx), length(gy))

if(density){z=z/(nx*pi*h^2)}

return=list(x = gx, y = gy, z = z)

}

It works in more or less the same way as kde2d, but by default it  
returns counts not densities

Aaron

Hello R users,

I have successfully created a square (or more generally, rectangular)
tophat smoothing routine based on altering the already available
KDE2D. I would be keen to implement a circular tophat routine also,
however this appears to be much more difficult to write efficiently (I
have a routine, but it's very slow). I tried to create one based on
using crossdist (in spatstat) to create a distance matrix between my
data and the sampling grid, but it doesn't take a particularly large
amount of data (or hi-res grid) for memory to be a big problem. The 2D
density routines I have been able to find either don't support a
simple tophat, or don't use the absolute distances between the
sampling grid and the data. Should anyone know of more general 2D
density routines that might support circular tophats, or know of a
simple and efficient method for creating them, I would be very  
grateful.

Thanks for your time,

Aaron

PS: I tried sending this on Friday originally, but as far as I know
that didn't work, so should another post appear from me asking the
same thing I apologise in advance.
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