similar to: read.table() code fails outside of the utils package

Rprof seems to ignore all time spent inside system() calls. E.g., this simple example actually takes about 10 seconds, but Rprof thinks the total time is only 0.12 seconds: > Rprof("sleep-system.out") ; system.time(system(command="sleep 10")) ; Rprof(NULL) user system elapsed 0.000 0.004 10.015 > summaryRprof("sleep-system.out")$by.total

For many years, when my R process starts up I've been automatically setting my preferred default plot colors, basically like so: my.colors <- c("black" ,"red" ,"gold" ,"sky blue" ,"green" ,"blue" ,"orange" ,"grey" ,"hot pink" ,"brown" ,"sea green" ,"cyan"

On Linux x86-64 (Ubuntu 6.06), the latest R sources from the Subversion trunk fail to build with the following "recompile with -fPIC" error: $ ./configure --with-x=yes --prefix=$inst_dir --enable-R-shlib --with-tcltk=/usr/lib/tcl8.4 --with-tcl-config=/usr/lib/tcl8.4/tclConfig.sh $ make /usr/bin/ld: ../appl/approx.o: relocation R_X86_64_32 against `a local symbol' can not be

I want to create my own "[" function (for use on vectors, matrices, arrays, etc.), which calls the stock R "[", does some additional work, and then finally returns the modified result. But, how do I properly call the stock R "[" function? It takes a varying number of positional arguments, and its R-level closure is just: .Primitive("[") It's

--rwEMma7ioTxnRzrJ Content-Type: text/plain; charset=us-ascii Content-Disposition: inline R, like recent versions of S-Plus, sometimes - but not always - loses names when subscripting objects with "[". (Earlier versions of S and S-Plus had the correct, name-preserving behavior.) This seems bad, it would be better to remove names only by explicit request, not as an accidental

I recently started using R 2.7.2, and noticed a surprising change in the behavior of var() on NA data: R 2.6.1 (Patched), 2007-11-26, svn.rev 43541, x86_64-unknown-linux-gnu: > stdev(rep(NA,3), na.rm=F) [1] NA > stdev(rep(NA,3), na.rm=T) [1] NA > var(rep(NA,3), na.rm=T, use="complete.obs") [1] NA R 2.7.2 (Patched), 2008-09-02, svn.rev 46491,

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

It would be nifty to incorporate this into R or into an R package: http://sourcefrog.net/projects/natsort/

>>>>> Andrew Piskorski >>>>> on Tue, 24 Oct 2023 00:01:58 -0400 writes: > In previous versions of R, Not in R 4.3.0 or 4.3.1 {you are a bit late with updating ..}. > as.character.Date() retained any names on > its input vector. In R 4.3.2 beta, it removes names. Is this change > intentional, or a bug? (For what it's

In versions of R prior to 3.0, by default .C and .Call would find the requested C function regardless of which shared library it was located in. You could use the PACKAGE argument to restrict the search to a specific library, but doing so was not necessary for it to work. R 3.0 introduced a significant change to that behavior; from the NEWS file: CHANGES IN R 3.0.0: PERFORMANCE

Today I built R from source on a 32-bit Ubuntu 10.04.3 LTS box, and saw that the "make check" tests/reg-tests-1b.R failed. From the output at the end of my "tests/reg-tests-1b.Rout.fail" file, the problem is appearing in the "identical(z, x %*% t(y))" test code below. I then tried the stock R provided by the Ubuntu r-base-core binary package, and to my surprise, it

What is the best code available for simple general purpose manipulation of tree (and/or directed graph) data structures in R? Looking through CRAN, I see a bunch of packages for stastical regression trees, but nothing that seems to provide an API for manipulating tree data structures. What I'm looking for is something along the lines of an R version of the Tcllib ::struct::tree API available

I'm currently using R CMD INSTALL to build and install some of my own custom R packages. Basically, I use a script which first builds a tarball of my R source code, and then calls R CMD INSTALL, which builds and installs that source package from the tarball, including re-compiling all my C code from scratch every single time, which is both totally unneccessary and tediously slow. What I

Dear all, I discovered that read.table (RW1.8.0) leaves out data when reading multiple-line records. Replication code at the end Best regards Jens Oehlschlägel > filename <- "c:/tmp/c2.csv" > > data <- data.frame(a=c("c", "e\nnewline"), b=c("d", '"quoted simpleline"')) > > #look at the data >

In the R-2-9-branch (svn revision 49914, 2009-09-24), R's configure script has an "--enable-threads" option. But, does it do anything useful? When I use "--enable-threads=posix", some of the configure output changes slightly, but it seems to have no effect on the actual link commands used when building R. Is that a bug, or am I misunderstanding what it's supposed to

R folks, I'm curious about possible support for Lisp-style macros in R. I'm aware of the "defmacro" support for S-Plus and R discussed here: http://www.biostat.wustl.edu/archives/html/s-news/2002-10/msg00064.html but that's really just a syntactic short-cut to the run-time use of substitute() and eval(), which you could manually put into a function yourself if you cared

Dear developers, is there (already) a platform-independent way for (temporarily!) changing the fpu control word? More precisely: I am looking for functions (accessible from C code in R packages) which read and write the fpu control word on x86 cpus (and cause no harm otherwise), because I need to (temporarily) turn off internal 80-bit precision for some algorithms relying on 64-bit IEEE

Dear R Users; Perl is the common language to write CGI scripts which handle Forms. My question is that can R be as fast as perl to do the same job(with using CGIwithR package). Is it an optimal solution to connect R directly to a commercial HTML webpages, Sincerely, Sean

Hi, Has anyone succeeded in cross-compiling R to Linux on an ARM CPU? If so, can you share a little about your toolchain & build process? Thanks! [[alternative HTML version deleted]]

I'd like to install several different versions of R from source. I'm doing this on Ubuntu Linux 6.06 Dapper x86-64, which ships with R 2.2.1, so the versions of R I want to use are (for now) 2.2.1, 2.4.x, and the development head. Fetching the sources with Subversion and running configure with something like "--prefix=/usr/local/R-2.4-branch-20061130" is straightforward, but