Andrew McFadden said the following on 3/12/2008 1:47 PM: > Hi all > > I am trying to determine the distances between two datasets of x and y > points. The number of points in dataset One is very small i.e. perhaps > 5-10. The number of points in dataset Two is likely to be very large > i.e. 20,000-30,000. My initial approach was to append the first dataset > to the second and then carry out the calculation: > > dists <- as.matrix(dist(gis data from 2 * datasets)) > > However, the memory of the computer is not sufficient. A lot of > calculations carried out in this situation are unnecessary as I only > want approx 5 * 20,000 calculations versus 20,000 *20,000. > > x <- c(2660156,2663703,2658165,2659303,2661531,2660914) > y <- c(6476767,6475013,6475487,6479659,6477004,6476388) > data2<-cbind(x,y) > > x <- c(266500,2611111) > y <- c(6478767,6485013) > data1<-cbind(x,y) > > Any suggestions on how to do this would be appreciated. > > Regards > > Andrew
If you're trying to find only the closest point in data1 to data2, then use knn (or knn1) in the 'class' package: library(class) nn <- knn1(data2, data1, 1:nrow(data2)) which gives you the rows in data1 closest to each row in data2. Then compute the distance: rowSums((data2[nn, ] - data1)^2)^0.5 HTH, --sundar ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
