From: Jose Quesada <quesada_at_gmail.com>

Date: Tue 23 Jan 2007 - 20:40:50 GMT

x[]

# this is actually a very large sparse matrix, but it doesn't matter for the

# example

library(Matrix)

x = as(dat,"CsparseMatrix")

Date: Tue 23 Jan 2007 - 20:40:50 GMT

Dear R users,

I want to apply a function that takes two vectors as input to all pairs (combinations (nrow(X), 2))of matrix rows in a matrix. I know that ideally, one should avoid loops in R, but after reading the docs for do.call, apply, etc, I still don't know how to write the nested loop in a vectorized way.

Example data:

x = matrix(rnorm(1000), 100, 100) zeros = runif(90)

x[]

# this is actually a very large sparse matrix, but it doesn't matter for the

# example

library(Matrix)

x = as(dat,"CsparseMatrix")

# cosine function

cosine = function (x, y){

if (is.vector(x) && is.vector(y)) { return(crossprod(x, y)/sqrt(crossprod(x) * crossprod(y))) } else {stop("cosine: argument mismatch. Two vectors needed as input.")}}

# The loop-based solution I have is:

if (is(x, "Matrix") ) { cos = array(NA, c(ncol(x), ncol(x))) # preallocate memory for (i in 2:ncol(x)) { for (j in 1:(i - 1)) { cos[i, j] = cosine(x[, i], x[, j]) } } }

This solution seems inneficient. Is there an easy way of achieving this with a clever do.call + apply combination?

-- Thanks in advance, -Jose -- Jose Quesada, PhD Research fellow, Psychology Dept. Sussex University, Brighton, UK http://www.andrew.cmu.edu/~jquesada ______________________________________________ R-help@stat.math.ethz.ch 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.Received on Wed Jan 24 07:49:23 2007

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