similar to: littler+dget+stdin -> segmentation fault

Hi, I'm trying to write R scripts using littler (under Debian), and was originally using the shebang line: #!/usr/bin/env r However this picks up any .RData file that happens to be lying around, which I find a little disturbing, because it means that the script may not behave the same way on successive invocations. If you drop the /usr/bin/env trick then #!/usr/bin/r --vanilla seems to

Hi (again), Another difficulty I'm having is creating a common function (foo, say) to share between two scripts. I've tried making a third file containing the function and then sourcing it with source ("foo.R"), but that only works if you run the script in the directory where "foo.R" is. (or if the scripts know where they're installed) The other solutions that

What ? ------ We are pleased to announce version 0.0.6 of littler What's new ? ------------ This version includes a bug fix or two as well as a number of small enhancements to the documentation. For OS X and the r/R confusion, our recommended suggestion is to call configure using either the --program-suffix=X or --program-prefix=Y option to have the binary and manual

What ? ====== littler - Provides hash-bang (#!) capability for R (www.r-project.org) Why ? ===== GNU R, a language and environment for statistical computing and graphics, provides a wonderful system for 'programming with data' as well as interactive exploratory analysis, often involving graphs. Sometimes, however, simple scripts are desired. While GNU R can be used

Hello list, I'm having some difficulty getting rJava to load in littler. Even after a R CMD javareconf and a reinstall of littler, I get this: jlaing at xenon:~$ r -e "require(rJava)" Loading required package: rJava Loading required package: methods Error : .onLoad failed in loadNamespace() for 'rJava', details: call: dyn.load(file, DLLpath = DLLpath, ...) error: unable

Dear R folks, I have several data sets I want to process automatically using R. I found littler [1] and thought this will do the trick. 1. Read in data file to a data frame using `scan()`. 2. Do linear regression. 3. Write the data and the coefficients back to a file. #!/usr/bin/env r if (is.null(argv) | length(argv)!=1) { cat("Usage:

Dear R folks, wanting to compare different implementations of a solution I want to script it to iterate over the different implementations. Is there a way to do this in the R shell/command line? $ more /tmp/iterf.r f1 <- function(n = 100000, l = 100000) { z = n + l } f2 <- function(n = 100000,

Hi, This code used to work well until a few months ago (I haven't used it since), but now it's giving this: ---<--------------------cut here---------------start------------------->--- $ cat <<EOF | r - locs <- read.csv(list.files(pattern="ds_.+_.+\\.csv"), colClasses=c(rep("character", 2), "numeric", "character",

Hi, I'm not sure when this started occurring, but now I get: ---<--------------------cut here---------------start------------------->--- $ r -e 'quantile(rnorm(1e5))' Error in (function (name, package, ...) : autoloader did not find 'quantile.default' in 'stats' ---<--------------------cut here---------------end--------------------->--- I'm using

Hello, I've noticed that dget() is much slower in the current and devel R versions than in previous versions. In 2.15 reading a 10000-row data.frame takes less than half a second: > (which.r <- R.Version()$version.string) [1] "R version 2.15.2 (2012-10-26)" > x <- data.frame(matrix(sample(letters, 100000, replace = TRUE), ncol = 10)) > dput(x, which.r) >

Full_Name: David States Version: 2.6.0 OS: Windows XP64 Submission from: (NULL) (141.211.38.9) # The pair of commands # # dput(object, "file.dput") # object = dget("file.dput") # # should be a no op, but this is not working correctly for all objects. # # Simple example: # # make a simple object of class "hclust" cl = hclust(dist(matrix(nrow=4,ncol=4, c(1:16)))) #

I am seeking advice about dput() and dget(). We are using the ascii format supported by these functions as a way to write data from other programs that can be read into R easily. We are able to save complicated results (in the form of an R list) to a single file that can be read trivially into R or S-Plus. My question is whether that format can be considered a safe one for medium-term (say

This doesn't seem right; I'm using R version 2.4.1 (2006-12-18) on Mac OS and Win XP and find the same issue: > mydataframe <- data.frame(ppi=c(.5,.5),mmu=c(5,10)) > dput(mydataframe,"mydataframe.txt") > dget("mydataframe.txt") Error in attributes(.Data) <- c(attributes(.Data), attrib) : row names must be 'character' or 'integer', not

Hi, I've been using r (the little, but sweet one!), and recently found out about the magic argv vector of the rest of arguments passed to it. How can we process an argument that represents elements of a vector: $ r littler_ex.R 14 '3, 2' Error in ff * ss : non-numeric argument to binary operator where: ,-----[ cat ~/scripts/R/littler_ex.R ] | ff <- as.numeric(argv[1]) | ss

MyBSD% ./configure checking for a BSD-compatible install... /usr/bin/install -c checking whether build environment is sane... yes checking for gawk... no checking for mawk... no checking for nawk... nawk checking whether make sets $(MAKE)... yes checking build system type... i386-unknown-freebsd6.2 checking host system type... i386-unknown-freebsd6.2 checking for a BSD-compatible install...

Hi. I would like to know how to start an embedded R session, and avoid datasets and the standard library packages to be loaded on startup. I've been looking at littler's code (so this is partly a question to Dirk Eddelbuettel...): > /* We don't require() default packages upon startup; rather, we > * set up delayedAssign's instead. see autoloads(). >

Dear useRs, This is to announce that the maintainers of the various distributions have decided to provide "experimental" up-to-date versions of the following R related packages on Debian stable and Ubuntu (i386 and amd64 architectures): littler rkward python-rpy (not on Ubuntu Dapper) python-rpy-doc (not on Ubuntu Dapper) By "experimental" we mostly mean that

Dear useRs, This is to announce that the maintainers of the various distributions have decided to provide "experimental" up-to-date versions of the following R related packages on Debian stable and Ubuntu (i386 and amd64 architectures): littler rkward python-rpy (not on Ubuntu Dapper) python-rpy-doc (not on Ubuntu Dapper) By "experimental" we mostly mean that

Hi, I have searched the archive for the solution of this question, but couldn't find anything, so I thought I would ask here. I am using R on a Debian (testing) system. Many of the R packages I use are installed as .deb packages, those which are not available in this format I install using install.packages. When calling update.packages, sometimes the R repository version is more recent

Hi, I have searched the archive for the solution of this question, but couldn't find anything, so I thought I would ask here. I am using R on a Debian (testing) system. Many of the R packages I use are installed as .deb packages, those which are not available in this format I install using install.packages. When calling update.packages, sometimes the R repository version is more recent