similar to: Behaviour of environment(foo)<- (PR#1509)

I find this a bit puzzling ... > solve(matrix(c(5, 2, 3, 1), 2, 2), c(Inf, 3)) [1] NaN Inf > solve(matrix(c(5, 2, 3, 1), 2, 2)) %*% c(Inf, 3) [,1] [1,] -Inf [2,] Inf I would expect the answer to be c(-Inf, Inf), so why has the -Inf been replaced by NaN in solve? Cheers, Jonathan. --please do not edit the information below-- Version: platform = sparc-sun-solaris2.7 arch = sparc

Hi everyone, I have noticed that is.vector returns FALSE if I attach attributes: > x <- c(a = 1, b = 2) > attributes(x) $names [1] "a" "b" > is.vector(x) [1] TRUE > attr(x, "fred") <- "happy" > attributes(x) $names [1] "a" "b" $fred [1] "happy" > is.vector(x) [1] FALSE This seems inconsistent to me,

The following commands z <- matrix(seq(0, 1, len=1000)) image(z, 1, z, zlim=c(0, 1), col=gray(1:10/10)) appear to violate the image functionality as described on the help page. As I understand it, by specifying a zlim of c(0, 1) and a colour vector of length 10, the colours should correspond to the intervals (0, 0.1), (0.1, 0.2), ..., (0.9, 1.0), this being 10 equally-spaced intervals on (0,

Jonathan Rougier <J.C.Rougier@durham.ac.uk> writes: > Would it be reasonable to suggest adding an `all' flag to save.image(), > i.e. > > "save.image" <- > function (f = ".RData", all.names = F) > eval(substitute(save(list = ls(all.names = all.names), file = f)), > .GlobalEnv) I believe this is simply a bug. I see no reason to skip the

Hi everyone, Two minor points about ?.Renviron. 1) If R_ENVIRON is not set then R defaults to `${R_HOME}/etc/Renviron', not `${R_HOME}/etc/Renviron.site' as stated. 2) In the details, there is a missing "way" in "`value' is processed in a similar to a Unix shell." Cheers, Jonathan. --please do not edit the information below-- Version: platform =

Here's a nasty one. The following has caused a segmentation fault and possibly also a bus error. fred <- 1:6 dim(fred) <- 6 dimnames(fred) <- list(LETTERS[1:6]) mm <- matrix(1:12, 2, 6) mm %*% fred # segmentation fault here In the case without the dimnames assignment the result is OK. Cheers, Jonathan. --please do not edit the information below-- Version: platform =

Dear List I am looking for the recommended way to create a formula inside a function with an empty environment. I tried several versions (see below), and one of them seemed to work, but I dont understand why there is a difference between .GlobalEnv and the environment inside a function. I would be greatful for any reference or explanation or advice. Thanks Thomas #+BEGIN_SRC R :results output

Hi everyone, The following code may not be very sensible, but it generates a core dump. The same happens in R-1.5.1. Cheers, Jonathan. arrow:dma0jcr% R-1.6.0 R : Copyright 2002, The R Development Core Team Version 1.6.0 (2002-10-01) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type `license()' or `licence()'

Hi everyone, I am following instructions here as I have generated the following warning: > # stuff looping through some plots with ask=TRUE Hit <Return> to see next plot: Hit <Return> to see next plot: Hit <Return> to see next plot: Hit <Return> to see next plot: Hit <Return> to see next plot: In addition: Warning message: An unusual circumstance has arisen

Hello, Suppose I have an expression, E, which accesses some variables present in an environment V. I do this via eval(E,envir=V) however all assignments end up in V. I would like the results of assignments in E to end up in the .GlobalEnv ? Or at least the calling environment. Is there a quick way to this instead of iterating over all objects E and assigning into .GlobalEnv? Thank you Saptarshi

In the below, I generate a model from an environment that isn't .GlobalEnv with a large object that is unrelated to the model generation. It seems to save the irrelevant object unnecessarily. In my actual use case, I am running and saving many models in a loop that each use a single large data.frame (that gets collapsed into a small data.frame for estimation), so removing it isn't an

Another solution is to only save the parts of the model object that interest you. As long as they don't include the formula (which is what drags along the environment it was created in), you will save space. E.g., tfun2 <- function(subset) { junk <- 1:1e6 list(subset=subset, lm(Sepal.Length ~ Sepal.Width, data=iris, subset=subset)$coef) } saveSize(tfun2(1:4)) #[1] 152 Bill

Hi Everyone, We have just upgraded to R-1.2.1, and I note, in contrast to R-1.1.1, that ctest is now loaded automatically. The mechanism for this is to create a .First function in base: .First <- function() { require("ctest", quietly=TRUE) } Now I don't want ctest, but I find that simply putting if (length(grep("ctest", search()))) detach(package:ctest) into

Hi Everyone, The following rather extreme claim on memory causes a segmentation fault on my installation: fred <- matrix(1:1200, 20, 60) littleOP <- function(x, y) { z <- as.vector(x) %*% t(as.vector(y)) dim(z) <- c(dim(x), dim(y)) z } littleOP(fred, fred) # this is OK littleOP(littleOP(fred, fred), fred) # whoops! Segmentation fault What's a bit strange

I get a segmentation fault as follows: > tmp <- array(list(), c(3, 4)) > tmp[[1, 2]] NULL # as expected > tmp[[1, 2]]$fred <- 1:10 > tmp # as expected [,1] [,2] [,3] [,4] [1,] "NULL" "List,1" "NULL" "NULL" [2,] "NULL" "NULL"

According to :https://stat.ethz.ch/R-manual/R-devel/library/base/html/environment.html "If |fun| is a function or a formula then |environment(fun)| returns the environment associated with that function or formula. If |fun| is |NULL| then the current evaluation environment is returned." > environment() <environment: R_GlobalEnv> > environment(environment)

Environment variables set with Sys.putenv() disappear (i.e. become "") after a while, especially after heavy-duty I/O. Example: R> x <- matrix(1., 3000, 3000) R> save(x, file="myx.RData") R> Sys.putenv(HOME="/tmp") R> while (Sys.getenv("HOME") != "") {cat("ok\n"); load("myx.RData")} The loop prints

The behaviour of within() with list input changes if you delete 2 or more variables, compared to deleting one: l <- list(x=1, y=2, z=3) within(l, { rm(z) }) #$x #[1] 1 # #$y #[1] 2 within(l, { rm(y) rm(z) }) #$x #[1] 1 # #$y #NULL # #$z #NULL When 2 or more variables are deleted, the list entries are instead set to NULL. Is this intended?

I was surprised to find that the variance of a scalar, using var(), is NA. Surely this should be zero? Cheers, Jonathan. --please do not edit the information below-- Version: platform = sparc-sun-solaris2.7 arch = sparc os = solaris2.7 system = sparc, solaris2.7 status = Patched major = 0 minor = 99.0 year = 2000 month = February day = 9 language = R Search Path: .GlobalEnv,

Hi all, I often keep code in separate files for organizational purposes, and source() that code from higher level scripts. One problem is that those sourced files often create temporary variables that I don't want to keep around. I could clean up after myself with lots of rm()'s, but that's a pain, and is messy. I'm wondering if one solution might be to source the code in a