similar to: R vs Python performance-wise

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

-----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 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

Hello, I would like to use my own dissimilarity matrix in a PAM clustering with method "pam" (cluster package) instead of a dissimilarity matrix created by daisy. I read data from a file containing the dissimilarity values using "read.csv". This creates a matrix (alternatively: an array or vector) which is not accepted by "pam": A call

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

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,

(Extremely sorry, disregard previous email as I hit send before pasting the latest version of the example; this one is smaller too) 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

(Extremely sorry, disregard previous email as I hit send before pasting the latest version of the example; this one is smaller too) 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

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

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'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

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 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, 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

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?

Hi, I'm finding a very strange error. For no good reason my R console (Rgui.exe, R 2.5.0, under win XP) stops producing anything meaningful, and just returns: Error: bad value to _whatever_ I enter. It starts doing this after a while, not immediately when launched. I have to restart R when this happens. No idea why. I didn't change anything in the R config that I remenber. Any

On Mon, 29 Jun 2020 at 14:25, Jos? Ab?lio Matos <jamatos at fc.up.pt> wrote: > > Again you guessed right, that was the main idea. :-) > As I told above and to reiterate it, the idea of this work is to make it easier to automate the > process. Similarly to how we do the mass builds for all the packages. But the mass rebuild process is very different, because releng doesn't

Followup of commit f190e08d85556dac293ef15bfeee38e54471570f. --- v2v/Makefile.am | 2 ++ v2v/test-v2v-o-json.sh | 58 ++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 60 insertions(+) create mode 100755 v2v/test-v2v-o-json.sh diff --git a/v2v/Makefile.am b/v2v/Makefile.am index 39511022e..1c37d20b4 100644 --- a/v2v/Makefile.am +++ b/v2v/Makefile.am @@ -468,6 +468,7 @@ TESTS