similar to: trellis graphics in loops

Hi all, I would like to draw one picture which would show two different types of boxplots using the same axes (kind of on top of each other). However, I would like to plot each boxplot using a different color or different shading inside the box, so they could be better distinquished from each other... Could you help me? Here is an example of the plot I have so far. I was only able to change the

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

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

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 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]]

Dear all, I have define a function and its methods as follows: ######## beginning of code fn <- function(x,...){ UseMethod("fn") } fn.foo1 <- function(x, commonA=1, ...){ print("fn.foo1 is called.") } fn.foo2 <- function(x, uniqueFoo2, common=1, ...){ ## uniqueFoo2 is a unique argument in fn.foo2 x <- uniqueFoo2; class(x) <- "foo1" ## use uniqueFoo2

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

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, some change during the last 10 days breaks code where slots of an object are changed globally: setClass("mylist", contains = "list") setClass("dummy", representation = representation( a = "mylist")) foo1 = function(i, x) { mydummy@a[[i]] <<- x ### change a slot } foo2 = function() { ### define an object mydummy <<-

Hi, I'm running postfix as SMTP-server and dovecot as IMAP-server. The server has multiple IPs, and postfix is configured that every domain is using a separate IPv4-address. Examle: foo1.com --> 11.22.33.44 foo2.com --> 22.33.44.55 foo3.com --> 33.44.55.66 bar.org --> 66.77.88.99 The hostname of the server is: mail.bar.org Now I have a request from one of my customers,

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 ------#

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

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(...)

On Mon, Dec 8, 2014 at 3:32 PM, Duncan Murdoch <murdoch.duncan at gmail.com> wrote: [...] > Why not declare colorspace as a "Suggests:" kind of dependency? I guess that is a solution. :/ In another example in the 'disposables' package I have: \donttest{ pkg <- make_packages( foo1 = { f <- function() print("hello!") ; d <- 1:10 }, foo2 = { f

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) {

Hi the list In the DESCRIPTION file of my package foo0, I have: Depends: foo1 Imports: foo2 Suggest: foo3 Enhence: foo4 If I understand correctly, to install foo0 on my computer, I need to already have foo1, foo2, foo3. foo4 is not necessary. I my R sesssion, when I will write: library(foo0), then the package foo1 will be attach. foo2, foo3 and foo4 will not. Is that correct? But what is

Dear R developers, Taking advantage of the yesterday discussion about the use of Depends/Import/Suggests/Enhances, I would like to add a related question. Let's assume, in the DESCRIPTION file of my package foo0, I have: Depends: foo1 Imports: foo2 while in the NAMESPACE file of my package I have importFrom("foo2", f2) and within my package I use the following two external

Hello, and sorry if this is already explained somewhere. I couldn't find anything. R (2.3.1, Windows) seems to perform some kind of lazy evaluation when evaluating defaults in function calls that, at least for me, leads to unexpected results. Consider the following, seemingly equivalent functions: > foo1 <- function(x, y=x) { + x <- 0 + y + } > foo1(1) [1] 0 > foo2

TBAA Question. Please consider the following test case. ---Snip-- struct B { int b1; int b2; }; struct C { int b1; }; struct A { int a1; struct C SC; int a2; }; int foo1(struct A * Aptr, struct B* Bptr) { int *a = &Aptr->SC.b1; *a=10; Bptr->b1 = 11; return *a; } int foo2(struct A * Aptr, struct B* Bptr) { Aptr->SC.b1=10; Bptr->b1 = 11; return