> Hi all, > Say I have a matrix A with dimension m x 2 and matrix B with > dimension n x 2. I would like to find the row in A that is closest to > the each row in B. Here's an example (using a loop): > > set.seed(1) > A <- matrix(runif(12), 6, 2) # 6 x 2 > B <- matrix(runif(6), 3, 2) # 3 x 2 > m <- vector("numeric", nrow(B))
make the lines below a function of a vector argument and apply it over the rows of B. ?apply for more info. You'll want to know about apply if you want to avoid loops (which is a good approach). > for(j in 1:nrow(B)) { > d <- (A[, 1] - B[j, 1])^2 + (A[, 2] - B[j, 2])^2 > m[j] <- which.min(d) > } > > All I need is m[]. I would like to accomplish this without using the > loop if possible, since for my real data n > 140K and m > 1K. I hope > this makes sense. Thing is, the above approach requires all data to be in main memory. i hope this is not a problem. ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html