similar to: dump not evaluating promises?

Hi All, I just used "dump" on Splus to transfer a pile of survival objects from Splus 3.4 on Solaris 7 to R 0.63.3 on Intel. The only trick is that survival objects contain an element holding the original call that generated the object. When Splus writes these out, it doesn't mark them in any way, so when R tries to read them in, it ends up trying to reevaluate the call. Not

Hi All, I just used "dump" on Splus to transfer a pile of survival objects from Splus 3.4 on Solaris 7 to R 0.63.3 on Intel. The only trick is that survival objects contain an element holding the original call that generated the object. When Splus writes these out, it doesn't mark them in any way, so when R tries to read them in, it ends up trying to reevaluate the call. Not

Hi, Sorry if this is already known... contour() sometimes draws contour lines that intersect. Is there a temporary fix? A dataset which causes problems is at http://www.maths.uwa.edu.au/~adrian/dumpdata.R If you try just source("dumpdata.R") image(huh) contour(huh) the 100 x 100 matrix 'huh' contains an hourglass-shaped region of values around 0.8. The contour plot

Hi I have within a quite big function foo1, an internal function foo2. Now, in order to have a cleaner code, I wish to have the internal foo2 as "external". This foo2 was using arguments within the foo1 environment that were not declared as inputs of foo2, which works as long as foo2 is within foo1, but not anymore if foo2 is external, as is the case now. Now, I could add all those

Greetings all, I am calculating two t-test values for each of many files then save it to file calculate another set and append, repeat. But I can't figure out how to write it to file and then append subsequent t-tests. (maybe too tired ;} ) I have tried to use "dump" and "file.append" to no avial. ttest_results = tempfile() two_sample_ttest <- t.test (tempA, tempB,

please see the code below. foo2 fails to dispatch correctly, but foo does fine. i have tried 'cacheMetaData(1)' and a number of different variants of 'cacheGenericsMetaData', on the possibility there is a caching issue. but i still can't sort it out. also one general question: does it really matter what's in the body of the function definition in a

Hello! Say I have a function foo1, which has argument ... to pass various arguments to foo2 i.e. foo1 <- function(x, ...) { foo2(x, ...) } Say that foo2 accepts argument arg1 and I would like to do the following: - if foo1 is called as foo1(x) then I would like to assign some value to arg1 inside foo1 before calling foo2 arg1 <- "some value" foo2(x, arg1=arg1) - if foo1 is

Thank you very much for your useful suggestions. These are exactly what I was looking for. foo <- list(foo1, foo2, foo3) lapply(foo, function(x) matrix(unlist(x), nrow = length(x), byrow = TRUE)) or lapply(foo, function(x) do.call('rbind', x)) Best, Muhammad Subianto On 4/11/06, Muhammad Subianto <msubianto at gmail.com> wrote: > Dear all, > I have a result my experiment

Dear R-devel, I'm trying to validate the results from a C function, against a (trial and tested) older R function. For reasons unknown to me, the C function seems to give different result sometimes at each trial, even with the very same data. These are the relevant outputs from R: > library(QCA) Loading required package: lpSolve > benchmark <- function(x, y) { + index <- 0

> tmp <- data.frame(y=rnorm(12), a=factor(rep(letters[1:4],3))) > tmp y a 1 -0.60866099 a 2 0.55500538 b 3 0.12231693 c 4 -0.24613790 d 5 -0.09253593 a 6 -1.54652581 b 7 0.17204210 c 8 -1.22778942 d 9 1.22151194 a 10 -0.43982577 b 11 -1.25444287 c 12 -0.97251060 d > tmp.aov <- aov(y ~ a, data=tmp) > summary(tmp.aov) Df Sum Sq Mean Sq F value

Dear all, I have a result my experiment like this below (here my toy example): foo1 <- list() foo1[[1]] <- c(10, 20, 30) foo1[[2]] <- c(11, 21, 31) foo2 <- list() foo2[[1]] <- c(100, 200, 300) foo2[[2]] <- c(110, 210, 310) foo3 <- list() foo3[[1]] <- c(1000, 2000, 3000) foo3[[2]] <- c(1100, 2100, 3100) list(foo1,foo2,foo3) The result: > list(foo1,foo2,foo3) [[1]]

This is a recent R-devel. file.copy() is not vectorized if multiple destinations succeed: cat("foo1\n", file = "foo1") cat("foo2\n", file = "foo2") unlink(c("copy1", "copy2"), recursive = TRUE) file.copy(c("foo1", "foo2"), c("copy1", "copy2"), copy.date = TRUE) #> Error in

Hi to all Authors@R: c(person("fooa","foob", role = c("aut","cre"), email = "fooa.foob@fooc.de"), person("foo1","foo2", role = c("ctb"), email = "foo1.foo2@foo3.de")) Author: fooa foob, with contributions from foo1 foo2 using r CMD check --as-cran .. (R 3.1

I've been trying to get plot.hclust to work with a hclust object I created and have not had much success. It seems that there is some "hidden" characteristic of a hclust object that I can't see. This is most easily seen in the following example, where plot.hclust works on one object, but when this object is "dumped" and then re-read, plot.hclust no longer works. Is

Hi, We've encountered a difference in running time between a straight function call and the same call using do.call when the called function generated an error. We've isolated the problem to the following small reproducible example: Consider the following function: foo <- function(nr = 2e6, nc=3, use.do.call = FALSE) { nn <- paste("V", 1:nc, sep="") z <-

Hi the list, I define a method that want to change an object without assignation (foo(x) and not x<-foo(x)) using deparse and assign. But when the argument of the method does not match *exactly* with the definition of the generic function, assign does not work... Anything wrong? Christophe #------ Does not work ------#

Hi all, For some reason, I would like to use functions bellow (see example code bellow), but instead I get the following error message: *Error in foo2(...) : unused argument(s) (arg3 = 3)* #--------------------- # example code #--------------------- foo1 <- function(arg1,...) { print(arg1) foo2(...) foo3(...) } foo2 <- function(arg2) { print(arg2) } foo3 <- function(arg3) {

I successfully used .Fortran to load and execute my fortran procedures under WinXP and 32 bit R. Alas, the same isn't true with my next Windows 7/64 machine, R 2.14.1 (64 bit) and the gnu gfortran (64) compiler (mingw64 v. 4.6.1). Though I'm able to compile the routines from the command line using gfortran '...', .Fortran('foo2') results in an error saying the Fortran

Dear List: In short, I am writing a number of functions as building blocks for other functions and have some questions about scoping and passing arguments. Suppose I have functions foo1, foo2, and foo3 such that: foo1<-function(a=1,b=TRUE,c=FALSE){#do stuff}; foo2<-function(x=1,y=FALSE,z=c(1,2,3,4)){#do stuff}; foo3<-function(lambda,...){lambda*foo1()*foo2()}; I want to be able to

Hi, although I've done S3 dispatching for more than a decade now, I think I managed to overlook/avoid the following pitfall when using NextMethod(): If you explicitly pass argument '...' to NextMethod(), you will effectively pass those argument twice to the "next" method! EXAMPLE: foo0 <- function(...) UseMethod("foo0"); foo1 <- function(...)