I want to
1) Select for each of the n points in a matrix A, those of the m points
in B that lay within a given radius.
2) Of those points within the radius, select the k nearest ones.
What I now do is
1) Create an n*m matrix C were I put the distances from all the points
in B to the points in A and make NA those cells were the distance is
larger than the radius. (The points are geographical locations so I use
function rdist.earth in package fields) e.g.:
library(fields)
data(ozone)
A<-cbind(ozone$lon.lat[1:10,])
B<-cbind(ozone$lon.lat+2)
C<-rdist.earth(A,B)
radius<-180 # The search radius
C[which(C>radius)]<-NA
2) Then I make NA everything but the k nearest ones
k<-5 # The nearest neighbours
rank<-function(rank){rank<-sort.list(sort.list(rank,))};
C[which(apply(C,2,rank)>k)]<-NA;
My problem is that the code is quite slow and due to the need to create
a n*m matrix I run out of memory many times. I would also prefer to get
a C matrix that is n*k instead of n*m were each of the values in C
indicated the row in B were the corresponding knearest point would be.
But I can not find a way to solve my main problem which is the need to
create a n*m matrix.
Thanks for any clues,
Angel
>- you could loop over the points in A using sapply so you don't store the huge matrix - R accepts logical indices -- you can eliminate which - R has a rank function so you don't need to define your own. You probably want to use the ties="first" or ties="random" arg in that. Angel Lopez <angel_lul <at> hotmail.com> writes: : : I want to : 1) Select for each of the n points in a matrix A, those of the m points : in B that lay within a given radius. : 2) Of those points within the radius, select the k nearest ones. : : What I now do is : 1) Create an n*m matrix C were I put the distances from all the points : in B to the points in A and make NA those cells were the distance is : larger than the radius. (The points are geographical locations so I use : function rdist.earth in package fields) e.g.: : library(fields) : data(ozone) : A<-cbind(ozone$lon.lat[1:10,]) : B<-cbind(ozone$lon.lat+2) : C<-rdist.earth(A,B) : radius<-180 # The search radius : C[which(C>radius)]<-NA : : 2) Then I make NA everything but the k nearest ones : k<-5 # The nearest neighbours : rank<-function(rank){rank<-sort.list(sort.list(rank,))}; : C[which(apply(C,2,rank)>k)]<-NA; : : My problem is that the code is quite slow and due to the need to create : a n*m matrix I run out of memory many times. I would also prefer to get : a C matrix that is n*k instead of n*m were each of the values in C : indicated the row in B were the corresponding knearest point would be. : But I can not find a way to solve my main problem which is the need to : create a n*m matrix. : Thanks for any clues, : Angel