similar to: [fixed] vectorized nested loop: apply a function that takes two rows

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

Dear R users, I need to normalize a bunch of row vectors. At a certain point I need to divide a matrix by a vector of norms. I find that the behavior of Matrix objects differs from normal matrix objects. Example the following code examples differ only in xnormed changing from normal to Matrix object: x = matrix(1:12,3,4) x = as(x, "CsparseMatrix") xnorms = sqrt(colSums(x^2))

Hi, I got the following error. Sorry but this time I couldn't reproduce it with a simple chunk of code: .TM.repl.i.2col(): drop 'matrix' case ... Error in .nextMethod(x = x, i = i, j = j) : 'i' has no integer column number should never happen; please report In addition: Warning messages: 1: Ambiguous method selection for "%*%", target

Hi, I'm finding that readMM() cannot read a file written with writeMM(). Example: library(Matrix) a = Matrix(c(1,0,3,0,0,5), 10, 10) a = as(a, "CsparseMatrix") writeMM(a, "kk.mm") b = readMM("kk.mm") Error in validObject(.Object) : invalid class "dgTMatrix" object: all row indices must be between 0 and nrow-1 Thoughts? Thanks, -Jose -- Jose

Hi, I need to multiply all columns in a matrix so something like apply(x,2,sum), but using multiplication should do. I have tried apply(x,2,"*") I know this must be trivial, but I get: Error in FUN(newX[, i], ...) : invalid unary operator The help for apply states that unary operators must be quoted. I tried single quotes too, with the same results. Thanks, -Jose -- Jose

Hi All, I recently found gmane http://gmane.org/ It's a system to covert mail to news and back, with the nice property of keeping a searchable archive... Very convenient if you are subscribed to many lists and don't want to have your mail box cluttered. I use it to read several mailing lists already, but R is not available there. I wonder if the admins know about gmane and if they

Dear all, I'm starting to learn R, but I'm already programing for a while, using ViM as editor. Therefore I'd like to be able to use R together with ViM. My question now is, whether there are already people out there knowing how to do this in a similar easy way as with Emacs, and if those would be willing to share this knowledge. I did already research on the web on this topic,

Hi, Has anyone run any R vs Python (numpy) tests? I'd love to see what the differences performance-wise are, specially handling large sparse matrices. Since both rely on external C code, there might not be much of a difference. If you know and use both languages, what are the main differences and what made you stick to one over another? I also noticed that there are strong libraries

Hi, Is there any simple solution to get ranks in descending order? Example, a <- c(10, 98, 98, 98, 99, 100) r <- rank(a, ties.method="average") produces 1 3 3 3 5 6 I would want this instead: 6 5 3 3 3 1 Note that reversing r doesn't work but in small examples. Thanks, -Jose -- jquesada at andrew.cmu.edu Research associate http://lsa.colorado.edu/~quesadaj Dept. of

Hi, I'd like to simply add column-wise using Matrix objects (Csparse). It looks like one can apply mosty any base function to these objects (i.e., apply, colSums), but there is a nasty conversion to traditional matrix objects if one does that. Is there any workaround? I can see colSum listed in the help for Class 'CsparseMatrix' , but I wonder whether I'm using the default

Hi, I'm attending summer School at UCLA (IPAM) on "probabilistics models of cognition". I have been an R-user since v. 1.4.1, but was trained in the frequentist tradition (as most psychologists!). I found that all faculty here use matlab and Murphy's bayes net toolbox. I have not had the need to use matlab before, and would love to stick to R for graphics models and

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi, I'm doing some basic operations on large sparse matrices, for example getting a row. it takes close to 30 seconds on a 3Ghz machine, and shots the memory usage up to the sky. I suspect there are dense intermediary steps (which, if true would defeat the purpose of trying to use sparse representaitons). As much as I try understanding the

Hi, I'm running this for a simulation study, so many combinations of parameter produce many predictions that I need to correlate with data. The problem ---------------- I'm using rating data with 3 to 5 categories (e.g., too low, correct, too high). The underlying continuous scales should be normal, so I chose the polychoric correlation. I'm using library(polychor) in its

Hi, I was wondering if anyone has had good experiences using R on Linux with dual AMD64 (Opteron) processors. I'm thinking of buying a couple of such servers, but I'd like to make sure R would work fine. The "R Installation and Administration" guide notes that there may be some problems with BLAS libraries. That's all I could find about R on AMD64. Please share your

Hi all: I have been using lighttpd on os x with RoR. It normally works great, however, when I use it for one project, kill the process, then switch to another project and start up using ./script/server, all I get is a blank page. No errors or html. The only solution I have found so far is to restart my machine, but that seems terribly inneficient. How does everybody else handle this, or do you

Hello, a. is there a possibility to obtain a distance matrix with the cosine between vectors?? hclust, hierclust, dist will not work and seem to be hard to extend. b. if there is not: Is the cosine between vectors implemented somewhere? Thanks for all hints and advice! Petra Steiner -------------- next part -------------- An HTML attachment was scrubbed... URL:

Hi, I'm trying to use a similarity matrix (triangular) as input for pam() or fanny() clustering algorithms. The problem is that this algorithms can only accept a dissimilarity matrix, normally generated by daisy(). However, daisy only accept 'data matrix or dataframe. Dissimilarities will be computed between the rows of x'. Is there any way to say to that your data are already a

I wrote a function to calculate cosine distances between rows of a matrix. It uses two loops and is slow. Any suggestions to speed this up? Thanks in advance. theta.dist <- function(x){ res <- matrix(NA, nrow(x), nrow(x)) for (i in 1:nrow(x)){ for(j in 1:nrow(x)){ if (i > j) res[i, j] <- res[j, i] else { v1 <- x[i,] v2 <- x[j,]

I have a pretty large sparse matrix of integers: > dim(tasa) [1] 91650 37651 I need to add one to it in order to take logs, but I'm getting the following error: > tasa = log(tasa + 1) CHOLMOD error: problem too large Error in asMethod(object) : Cholmod error `problem too large' I have 2 Gb of RAM, and the current workspace is barely 300mb. Is there any workaround to this?

I have a pretty large sparse matrix of integers: > dim(tasa) [1] 91650 37651 I need to add one to it in order to take logs, but I'm getting the following error: > tasa = log(tasa + 1) CHOLMOD error: problem too large Error in asMethod(object) : Cholmod error `problem too large' I have 2 Gb of RAM, and the current workspace is barely 300mb. Is there any workaround to this?