similar to: Unexplained difference between results of dppsv and dpotri LAPACK routines

This isn't the help list for LAPACK, but as far as I can tell, dppsv expects a symmetric matrix input compacted as triangular, not a Choleski decomposed one. So try assigning lmat before the call to dpotrf. -pd > On 20 Dec 2014, at 22:06 , Pierrick Bruneau <pbruneau at gmail.com> wrote: > > Dear R contributors, > > Considering the following sample C code, that

I give up. Maybe it is my search (Windows) but I cannot seem to find the definition of the F77_CALL or F77_NAME macros. Either there are too many matches or the search just doesn't find it. For example where is the source for: F77_CALL(dpotri) ? Thank you. Kevin

Hello all, In a piece of c++ code (part of a future R package), I'm inverting a relatively large covariance matrix many times using: F77_CALL(dpotrf)(&upper, &xnrow, R, &xnrow, &info); F77_CALL(dpotri)(&upper, &xnrow, R, &xnrow, &info); I am sure that the input matrix is PD and inverts just fine. However, I have found that dpotri gives one or more NaNs from

Dear R contributors, I'm running into trouble when trying to allocate some large (but in theory viable) vector in the context of C code bound to R through .Call(). Here is some sample code summarizing the problem: SEXP test() { int size = 10000000; double largevec[size]; memset(largevec, 0, size*sizeof(double)); return(R_NilValue); } If size if small enough (up to 10^6), everything is

I'm using .Call() to call C code from R under Windows (on an Intel Core 2 duo). The C code involves some very small numbers, and I think I'm losing precision using doubles. I thought I might use long doubles to see if I can get that precision back. I have a few questions: 1. Does this affect the portability to other OSs or processors? 2. I'm returning the results in a matrix. Will

Hi everyone, I am using eigen() to extract the 2 major eigenpairs from a large real square symmetric matrix. The procedure is already rather efficient, but becomes somehow slow for real time needs with moderately large matrices (few thousand lines). The R implementation statically extracts all eigenvalues (and optionally associated eigenvectors). I heard about optimizations of the eigen

I have a stupid problem that is currently driving me crazy... Let us suppose that I want to draw a big red square in the middle of my current device (say X11) I tried the following code : pushViewport(viewport(xscale=c(0,1), yscale=c(0,1)), just=c("center", "center")) vp1 <- viewport(x=unit(0.5, "native"), y=unit(0.5, "native"), width=unit(0.4,

Hello all. I'm developing a package for R holding a Gibbs sampler, which tends to have better performance when written in C than in R. During each iteration in the Gibbs sampler, I need the inverse of a symmetric matrix. For this, I wish to use lapack, as is concisely suggested in "Writing R extensions", since this will have better performance than I could ever write myself. After

Hi everyone, I am fairly new to R, and I am aware that others have had this problem before, but I have failed to solve the problem from previous replies I found in the archives. As this is such a standard procedure in psychological science, there must be an elegant solution to this...I think. I would much appreciate a solution that even I could understand... ;-) Now, I want to calculate a

Full_Name: Elizabeth Purdom Version: 1.9.1 OS: Windows XP Submission from: (NULL) (171.64.102.199) It would be great if heatmap and/or image had the option of printing a legend bar on it somewhere that would indicate the ranges given by the colors in the heatmap (i.e. a very small image rectangle with the same colors as in the heatmap). Because heatmap is using layout, it seems pretty

Hi, I'm writing an R package using the C code i've written. I'm wondering if anyone knows an easy way to calculate an inverse and cholesky factor of a matrix using the Fortran/C library of R: and how to call them from C. My code is based on the Numerical Reciepe code, and I'm trying to use something that is already in R. Thanks for your help in advance, Kosuke

r-devel list, I have recently written an R package that solves a linear least squares problem, and computes the multivariate normal density function. The bulk of the code is written in C, with interfacing code to the BLAS and Lapack libraries. The motivation here is speed. I ran into a problem computing the determinant of a symmetric matrix in packed storage. Apparently, there are no explicit

Hello again, lately I have been playing a lot with heatmap functions, in particular I complemented heatmap.2 with a nice feature from heatmap.plus, i.e. the possibility of assigning a matrix to ColSideColors so to take into account more annotations. Below is the code I introduced in heatmap.2, everything else is maintained equal to heatmap.2: if (!missing(ColSideColors)) { #if

Does anybody know how to deffine in the test tukeyHSD the pairs of comparison that you want to get? It is throw the lmat commnad, but I don't know the correct usage... Thanks a lot! Jos? -- MSc Jos? Alberto F. Monteiro Botanisches Institut Universit?t Basel ?????? ?????

Hi all, im triyng to implement a bayesian model with R and c++. I have a strange problem. I can't reproduce the error with a small script and then i post the original one. The problem is after the line for(MCMC_iter2=0;MCMC_iter2<thin;MCMC_iter2++) For the first 34 iterations all work fine, after, all the simulations of mu_acc_P return an "nan". If i delete the line

Dear R contributors, Say I want to debug some C code invoked through .Call() - say "varbayes" in the VBmix package. following the instructions in "Writing R Extensions", I perform the following actions : R -d gdb run library(VBmix) CTRL+C break varbayes signal 0 mod <- varbayes(as.matrix(iris)[,1:4], 2) The breakpoint is indeed activated, seemingly at the correct position

Hello everyone, Considering the following code sample : ---- indexes <- function(vec) { vec <- which(vec==TRUE) return(vec) } mat <- matrix(FALSE, nrow=10, ncol=10) mat[1,3] <- mat[3,1] <- TRUE ---- Issuing apply(mat, 1, indexes) returns a 10-cell list, as expected. Now if I do: ---- mat[1,3] <- mat[3,1] <- FALSE apply(mat, 1, indexes) ---- I would expect a

Hi! My boss asked me to be able to share some directories on a FreeBSD Samba server with users already created (and used) on a NT 4.0 PDC server. So I followed http://www.sugoi.org/bits/index.php?bit_id=10 I just replaced the Windows 2k part by adding the NetBIOS name of the machine to the NT PDC. When I did the smbpasswd trick it worked like charm: testsmb# smbpasswd -j CH-DOMAIN -r PDC

On 2020-07-15 14:36, Dirk Eddelbuettel wrote: > > G?ran, > > This is not an easy email to reply to because it _contains nothing > reproducible_. Thanks Dirk, Sorry about that, but my real question was (see below): "Is the problem that openblas uses C versions of blas?" That is, do I need to change F77_CALL(name)(...); to cblas_name(...); everywhere? And if so, is

Dear All, I have just updated R to the version 2.6.2 on F8 (with the official F8 rpm). However, when running as root the following command: update.packages(checkBuilt=T) I get a bunch of errors like the ones below. Any ideas? Thanks in advance, Paul ----------------------------------------------- * Installing *source* package 'nlme' ... ** libs gcc -m32 -std=gnu99 -I/usr/include/R