similar to: class

Dear R-developers I came across the following issue, which I find strange: setClass("A", representation(a = "numeric")) B <- list() myA <- new("A", a = 1) B$otherA <- myA B$otherA at a <- 2 myA at a Assigning a new value to slot 'a' in the _copy_ of myA stored in B$otherA changes the original value of myA -- this was surprising to me, and I

Hi, Given a simple three class hierarchy: A <-- B <-- C I want to define an initialize method for each class such that when I call new("C", x=5), the initialize methods for A and B are used to incrementally build the object. When I do what seems obvious to me using callNextMethod, I get an infinite recursion. An example follows... setClass("A",

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(...)

I have another problem with NextMethod. Not sure if its related to the last problem. In this example, we have a generic called ff with methods for AsIs and test classes. We call the generic with an object of AsIs class. The corresponding method adds 1 to it and then changes the class to test followed by issuing a NextMethod. However, that results in this error (using R 2.0.0, 2004-10-04

S Programming by Venables and Ripley (page 78) has the example listed at the end of this email. However, I get the following error when I try the example. I don't understand the descriptions of NextMethod on its help page. Could somebody let me know how to fix the error of this example? > test(x) c1 c2 Error in NextMethod() : no method to invoke Calls: test -> test.c1 -> NextMethod

The example is invoking NextMethod via an anonymous function, which is not allowed (see documentation for NextMethod). Normally one gets a runtime error "'NextMethod' called from an anonymous function", but not here as the anonymous function is called via do.call. I will fix so that there is a runtime error in this case as well, thanks for uncovering this problem. I

On 02/22/2018 12:07 PM, I?aki ?car wrote: > 2018-02-22 10:29 GMT+01:00 Tomas Kalibera <tomas.kalibera at gmail.com>: >> The example is invoking NextMethod via an anonymous function, which is not >> allowed (see documentation for NextMethod). > Thanks for your response. I definitely missed that bit. > >> Normally one gets a runtime >> error

Hello, I see some people including myself confused by the different object-oriented approaches in R (S3, S4, OOP, R.oo etc.). Would it be ok to collect examples and solutions for the different OO-packages in one package and add a vignette for documentation? (assuming I find time for this task) I mean in this case the package would not add data or functionality to R or serve as a companion

>> One clear moral seems to be don't do anything more inside a >> generic function than you really need to do. Keep it *very* >> simple indeed. >> > I recall JMC saying something like, all generic functions > should be one line long; a call to the appropriate UseMethod. It certainly is encouraging to know that others also have been confused by aspects of

Hello R list members, I have a good object-oriented programming and software engineering background (mostly Java) and know some R. I'd like to learn more about functional programming concepts and its support and application in R. Do you have any recommendations (books, links etc)? I read (and like) "Programming in Scala" (Odersky) and just ordered "Funktionale

"[.ggobiDataset" <- function(x, ..., drop=FALSE) { x <- as.data.frame(x) NextMethod("[", x) } "[[.ggobiDataset" <- function(x, ..., drop=FALSE) { x <- as.data.frame(x) NextMethod("[[", x) } "$.ggobiDataset" <- function(x, ..., drop=FALSE) { x <- as.data.frame(x) NextMethod("$", x) } > class(x) [1]

I'd like to have a class A that computes a likelihood, and a subclass B that computes the same likelihood by sometimes throws in an additional term (B includes measurement error). So B's likelihood needs to call A's, and then (sometimes) multiply by an additional term. It sounds as if, in the S3 scheme, NextMethod is supposed to do this: like.A <- function(stuff) compute value

Hi all, I'd like to ask if the following behavior is a bug. To me it certainly feels surprising, at the very least. In this example, I would like to call NextMethod() from my `child` object, have `cols` be left untouched, and then substitute(cols) in the parent method. It works when you use a `parent` object (as expected), but I would have also expected to get `mpg` back when calling it from

Hi all, Not sure if this belongs to R-devel or R-package-devel. Anyways... Suppose we have objects of class c("foo", "bar"), and there are two S3 methods c.foo, c.bar. In c.foo, I'm trying to modify the dots and forward the dispatch using NextMethod without any success. This is what I've tried so far: c.foo <- function(..., recursive=FALSE) { dots <-

My question is when the object argument of NexthMethod be used? In the following example, weather object argument is used will not affects the result. ### foo=function(x) {UseMethod("foo")} foo.cls1=function(x) { x=x+1;class(x)<-"ncls" NextMethod() } foo.ncls=function(x) { cat("ncls\n") } foo.cls2=function(x) { cat("cls2\n");print(x) }

Dear Prof. John Fox, ? Sat, 21 Sep 2024 12:47:49 -0400 John Fox <jfox at mcmaster.ca> ?????: > NextMethod(formula(object), data=eval(object$call$data), > contrasts.arg=object$contrasts) The use of NextMethod worries me a bit. It will work as intended as long as everyone gives fully-named arguments to the generic, without relying on positional or partial

Dear list members, After further testing, I found that the following simplified version of model.matrix.lme(), which omits passing xlev to the default method, is more robust. The previous version generated spurious warnings in some circumstances. model.matrix.lme <- function(object, ...){ data <- object$data if (is.null(data)){ NextMethod(formula(object),

R : Copyright 2001, The R Development Core Team Version 1.3.1 (2001-08-31) > tmp <- factor(1:3) > get("print.factor")(tmp) [1] 1 2 3 Levels: 1 2 3 > print.a <- function(x,...) { + print("this is a") + NextMethod("print", x, quote = FALSE, right = TRUE, ...) + } > > get("print.a") function(x,...) { print("this is a")

Hi all, I think there's an unnecessary line in [.Date which has a considerable impact on performance when subsetting large dates: x <- Sys.Date() + 1:1e6 microbenchmark::microbenchmark(x[1]) #> Unit: microseconds #> expr min lq mean median uq max neval #> x[1] 920.651 1039.346 3624.833 2294.404 3786.881 41176.38 100 `[.Date` <- function(x, ...,

Can someone help me understand the following behavior of "[<-" ? If I define a simple class based on a matrix, the [<- operation only inserts into the first column: > x <- matrix(rnorm(10),nrow=5,ncol=2) > class(x) <- "foo" > "[<-.foo" <- function(x, i, j, value) { + if(missing(i)) i <- 1:nrow(x) + if(missing(j)) j <-