similar to: R-alpha: eigen and batch

eigen(matrix(rep(1,9),ncol=3),only.values=T) works repeatedly but eventually (after 3 or 4 goes) gave a core dump of 11mb (I think only the first answer was right). if I type gc() immediately after the first call, I get a core dump right away (this might possibly be related to my huge core dumps with nlm) eigen(matrix(rep(1,9),ncol=3)) core dumps immediately after the first call Jim

I am having some difficulties using dynamically loaded C functions on a Sparc 10 with R compiled using cc (both R-0.49 and R-0.50). I get sporadic errors with the error message: Error: character variables must be duplicated in .C/.Fortran, with C functions which pass character variables. my C functions look like: anyfunc(char **filename, other variables ) This error message appears about 25%

I am having some difficulties using dynamically loaded C functions on a Sparc 10 with R compiled using cc (both R-0.49 and R-0.50). I get sporadic errors with the error message: Error: character variables must be duplicated in .C/.Fortran, with C functions which pass character variables. my C functions look like: anyfunc(char **filename, other variables ) This error message appears about 25%

Full_Name: Albrecht Gebhardt Version: 0.90.0 OS: osf4.0 Submission from: (NULL) (143.205.61.73) I had to apply the following patch to be able to compile on an alpha with DU 4.0E: ############################################### --- ./src/main/gram.y.mkString-patch Tue Nov 23 12:16:29 1999 +++ ./src/main/gram.y Tue Nov 23 12:16:59 1999 @@ -56,7 +56,8 @@ SEXP mkFloat(char *); SEXP

I've been inspired to look at the R source code by some strange timing results that I wrote about on my blog at radfordneal.wordpress.com (see the posts on "Speeding up parentheses..." and "Two surprising things...". I discovered that the strange speed advantage of curly brackets over parentheses is partially explained by an inefficiency in the evalList and

Hi, I am using eigen to get an eigen decomposition of a square, symmetric matrix. For some reason, I am getting a column in my eigen vectors (the 52nd column out of 601) that is a column of all NAs. I am using the option, symmetric=T for eigen. I just discovered that I do not get this behavior when I use the option EISPACK=T. With EISPACK=T, the 52nd eigenvector is (up to rounding error) a

Hello Group, I could use an advice on how SEXP handles work. My aim is to implement a system where I initially set a few global variables that are used for communication between C and R code. Then I do some work with R code and periodically call a function of my own that will update the system state. Such a design is useful for many purposes (for GUIs to name one). I am not entirely sure that R

Hi all, I've been writing a package and I've run into a problem that I'm unsure how to solve. I am looking to pass a C++ class object to R so that it may be passed back to another C++ function later on to be used. I'm quite new to R and this is my first time writing a package, so I hope you can bear with me. The following is how I create the class and use

Hi, All: Attached please find a symmetric, indefinite matrix for which 'eigen(...)$vectors' included NAs: > load("eigenBug.Rdata") > sum(is.na(eigen(eigenBug)$vectors)) [1] 5670 > sessioninfo() Error: could not find function "sessioninfo" > sessionInfo() R version 2.4.1 (2006-12-18) i386-pc-mingw32 locale: LC_COLLATE=English_United

Hello, I am writing an R/Go interoperability tool[1] that work similarly to Rcpp; the tool takes packages written in Go and performs the necessary Go type analysis to wrap the Go code with C and R shims that allow the Go code to then be called from R. The system is largely complete (with the exception of having a clean approach to handling generalised attributes in the easy case[2] - the less

Dear developers, is it possible to create environments in C code of packages? Simply using SEXP env; PROTECT (env = allocSExp(ENVSXP)); and assigning the enclosing environment with SET_ENCLOS seems to be insufficient. Best wishes, Martin -- Dr. Martin Becker Statistics and Econometrics Saarland University Campus C3 1, Room 206 66123 Saarbruecken Germany

I'm using external pointers and seemingly leaking memory. My determination of a memory leak is that the R process continually creeps up in memory as seen by top while the usage as reported by gc() stays flat. I have isolated the C code: void h5R_allocate_finalizer(SEXP eptr) { Rprintf("Calling the finalizer\n"); void* vector = R_ExternalPtrAddr(eptr); free(vector);

Ok, Here's the c code that's loaded into R as dll on windows: #include <R.h> #include <Rdefines.h> SEXP test1(SEXP col); SEXP test1(SEXP col) { SEXP col2; Rprintf("no value!\n"); return col2; } Compiles ok with bcc32 into a dll, loads into R as part of a library, I Run library(rkdb), then > .Call("test1", 2) no value! And puf! Rterm crashes.

Hi all, Hi, When I want to compute the eigenvalues & eigenvectors of a specific matrix, R crashes (i.e. it stops responding to any input). I've tried it with different versions of R (2.1.1, 2.2.0, 2.2.1) - all with crashing as result. What I did before the crash was: M <- as.matrix(read.table("thematrix",header=T)) eigen(M) If, instead of eigen(M), I use eigen(M,

Hi all, Recently our statistics students noticed that their Gibbs samplers were crashing due to some NaNs in some parameters. The NaNs came from mvrnorm (Ripley & Venables' MASS package multivariate normal sampling function) and with some more investigation it turned out that they were generated by function eigen, the eigenvalue computing function. The problem did not seem to happen

Hello, I?m trying to leverage R_ToplevelExec to implement C level try/catch. The way it is implemented allows for running a function in a top level context. This context gets an empty handler stack, so either the function runs correctly or it jumps. When it jumps, it does not find a handler, so it jumps to the top level context. R does not allow me to call begin context and end context

Hello, (This is follow up from this thread: http://www.nabble.com/execution-time-of-.packages-td22304833.html but with a different focus) I am often confused by the result of the profiler, when a loop is involved. Consider these two scripts: script1: Rprof( ) x <- numeric( ) for( i in 1:10000){ x <- c( x, rnorm(10) ) } Rprof( NULL ) print( summaryRprof( ) ) script2:

Hi, It seems that new("externalptr") is always returning the same instance, and not a new one as one would expect from a call to new(). Of course this is hard to observe: > new("externalptr") <pointer: (nil)> > new("externalptr") <pointer: (nil)> since not a lot of details are displayed. For example, it's easy to see that 2

For using R's .Call interface to C functions, all the examples I've seen have the C function return type SEXP. Why? What does R actually do with this return type? What happens if I *don't* return a SEXP? Reason I ask, is I've written some R code which allocates two long lists, and then calls a C function with .Call. My C code writes to those two pre-allocated lists, thus, I

Hello, I'm evaluating this expression expression({ for(x in 1:5){ .Call('rh_status','x') }}) a million times from a program with R embedded in it. I have attached reproducible code that crashes with Program received signal SIGSEGV, Segmentation fault. 0x00002b499ca40a6e in R_gc_internal (size_needed=0) at memory.c:1309 1309 FORWARD_NODE(R_PPStack[i]); Current language: