similar to: error handling

Along with getting pqR to work on Windows, I've also been testing it in the context of embedded R, and in the process have found some problems with the examples given of embedded R use. One problem can be seen in R_ReplDLLinit, in src/main/main.c: void R_ReplDLLinit(void) { SETJMP(R_Toplevel.cjmpbuf); R_GlobalContext = R_ToplevelContext = R_SessionContext = &R_Toplevel;

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:

I was debugging a problem reported to me regarding PL/R, and found that I can duplicate it using only R sources. It might be characterized as possibly a misuse of the findFun() function, but I leave that for the R devel experts to decide. The below results are all with R-2.5.1 (I can't seem to download r-patched at the moment, but didn't see anything in the 2.5.1-patched release

I'm having difficulty with Rprof. I have a documentation example test.qss that runs fine without profiling, but under Rprof, > Rprof() > source("test.qss") Error in standardGeneric("model.matrix") : UseMethod used in an inappropriate fashion Luke wrote about a similar circumstance last summer: # From: Luke Tierney (luke@stat.umn.edu) # Date: Fri Jul

Hi Consider the following example: f <- function(expr) g(expr) g <- function(expr) { ? h(expr) } h <- function(expr) { ? expr # evaluation happens here ? i(expr) } i <- function(expr) { ? expr # already evaluated, no costs here ? invisible() } rprof <- tempfile() Rprof(rprof) f(replicate(1e2, sample.int(1e4))) Rprof(NULL) cat(readLines(rprof), sep = "\n") #>

Hello, I would like to establish top level condition handlers and restarts, so that I don't explicit calls to withCallingHandlers and withRestarts in many places: For example : > customError function( message ){ err <- simpleError( message ) class( err ) <- c( "customError", class( err) ) err } > withCallingHandlers( { signalCondition(customError(

I'm picking up this 5-year old thread. 1. About the four memory allocations without a stacktrace I think the four memory allocations without a stacktrace reported by Rprofmem(): > Rprofmem(); x <- raw(2000); Rprofmem("") > cat(readLines("Rprofmem.out", n=5, warn=FALSE), sep="\n") 192 :360 :360 :1064 :2040 :"raw" are due to some

A common need in R frontends is to provide some sort of read, (parse), evaluate, print loop. However, there are also a number of points where frontends may want to differ from the standard REPL as available e.g. in R_ReplDLLdo1(). First some thoughts on what is needed, and what is already there, or missing. If you want to skip over this, a short summary is provided in the second half, below

Hello, When using R_tryEval (from JRI in my case), is there a way to setup error recovery strategy and more generally calling handlers. From my reading of context.c, R_tryEval calls R_ToplevelExec which creates a context like this: begincontext(&thiscontext, CTXT_TOPLEVEL, R_NilValue, R_GlobalEnv, R_BaseEnv, R_NilValue, R_NilValue); so I guess what I am trying to do is add

I'm trying to clarify contexts and their uses. I do have a good general understanding of them. My question is about "undeclared" and "non-existant" contexts. If I have a block somewhere (in sip.conf, for example), and it has no "context=thiscontext" field, does it just automatically use the "default" context? Or is this settable? (I see there is an

Dear R developers, i've got a question concerning an embedded R instance. I called the initialization routines as seen in the "writing extensions" guide (Rf_initialize, setup_Rmainloop and R_ReplDLLinit). I also changed the function callback pointer of readconsole and writeconsoleex to my local functions. when i call mainloop there is no problem and the commands are evaluated

The Rprofmem facility is currently enabled only if the configuration option --enable-memory-profiling is used. However, the overhead of having it enabled is negligible when profiling is not actually being done, and can easily be made even smaller. So I think it ought to be enabled all the time. I've attached a patch doing this, which also makes a number of other improvements to Rprofmem,

While doing some embedded programming and trying to figure out how to generate a hand coded SEXP equivalent of the line "t.test(x,conf.level=(1-p))$conf.int[2]" I had an idea for an addition to the embedded API. There are a number of hidden or static parse functions (R_ParseBuffer, R_Parse1Buffer, etc.) which take an IoBuffer* and returns a parsed tree. If one or more of these

I am compiling the Embedding examples in the tests directory and get an undefined reference. I include the make output as well as grep'd output of nm on libR.so and compiler and arch information. Do I have an improperly built R shared library or is there a problem with the Embedding tests or something else I am not seeing? Thanks for any help! George ost at

Full_Name: Jelle Goeman Version: 1.9.0 OS: mingw32, windows 2000 Submission from: (NULL) (145.88.209.33) Hi Everyone, I get very strange results using the function hasArg with the ... function argument. In my own function: > gt <- globaltest(X,Y) > sampling(gt) works fine, but > sampling(globaltest(X,Y)) results in: Error in eval(expr, envir, enclos) : "missing"

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%

I noticed this oddity about R profiling and setMethod. First, I "test out" Rprof. > require(methods) Loading required package: methods [1] TRUE > > Rprof("test.out") > data.frame("a") X.a. 1 a > Rprof(NULL) So far, so good. Next, I define myClass. > setClass("myClass", representation(mySlot = "numeric")) [1]

As far as I can see sys.on.exit() does not work. The following will give a non-null result in S, and seems about the simplest possible usage. test <- function() { on.exit(print(1)) ex <- sys.on.exit() str(ex) cat("exiting...\n") } > test() NULL exiting... [1] 1 Looking at the code suggests that on.exit is installing the code in a different context from the one

Hello, I'm trying to make my Java application work with R, which involves sending and retrieving data and to run R functions from within the Java application. I also need to have "live interaction" with R, to show the R console output (e.g. warnings and print) and to enable the user to enter input when a function asks for it. Therefore I created a simple R console in Java using JRI