similar to: package `methods' has persistent effects even if detached (PR#1715)

Thank you Gabriel, Agree, although I think that could be relaxed in this single case and AsIs class could be ignored. Best, Jan On Sun, Mar 29, 2020 at 7:09 PM Gabriel Becker <gabembecker at gmail.com> wrote: > > Jan, > > I believe it's because it has "a non-NULL attribute other than names" as per the documentation. In this case its class of "AsIs". >

This seemed too advanced for r-help and is related to the recent discussion of character vectors in dataframes. Following Brian Ripley's most excellent advice, we are moving to a world in which character vectors in dataframes are always of class AsIs. The cool way of doing this seemed to be the following: > cat(c("x", "y", "z"), file = "test.txt",

SVN?revision?77401?changes ????????x[isM]?<-?lapply(x[isM],?function(o)?`class<-`(o,?class(o)[class(o)?!=?"AsIs"])) to ????????x[isM]?<-?lapply(x[isM],?function(o)?`class<-`(o,?class(o)[!inherits(o,"AsIs")])) in?function?'get_all_vars'?in?src/library/stats/R/models.R?in?R?devel. The?change?is?inappropriate.

>>>>> Martin Maechler >>>>> on Mon, 18 Nov 2019 12:15:38 +0100 writes: >>>>> suharto anggono--- via R-devel >>>>> on Sun, 17 Nov 2019 10:34:31 +0000 writes: >> SVN revision 77401 changes >> x[isM] <- lapply(x[isM], function(o) `class<-`(o, class(o)[class(o) != "AsIs"])) >> to

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

? Fri, 12 Jul 2024 17:35:19 +0200 Hilmar Berger via R-devel <r-devel at r-project.org> ?????: > This can be finally traced to base::rank() (called from > xtfrm.default), where I found that > > "NB: rank is not itself generic but xtfrm is, and rank(xtfrm(x), ....) > will have the desired result if there is a xtfrm method. Otherwise, > rank will make use of ==, >,

Good evening, I recently have observed slow merges when combining multiple data frames derived from DataFrame and base::data.frame. I observed that the index column of intermediate tables was of class <AsIs> (automatically converted from character). The problem occurred mainly when using the sorted = T option in base::merge. This can be traced to xtfrm.AsIs being more than 100 times slower

Hi Martin, On 10/26/20 04:52, Martin Maechler wrote: >> >> Hi there, >> Is that change in R-devel intentional? >> >> library(Matrix) >> m <- as(matrix(c(0, 1)), "sparseMatrix") >> >> isS4(m) >> # [1] TRUE >> >> x <- I(m) >> # Warning message: >> # In `class<-`(x,

Dear R-devel, AsIs class seems to be well handled by `typeof` and `mode` function. Those two functions are being referred when explaining `is.vector` behaviour in manual. Yet `is.vector` does not seem to be handling AsIs class the same way. is.vector(1L) #[1] TRUE is.vector(I(1L)) #[1] FALSE Is there any reason behind this behaviour? Could we have it supported so AsIs class is ignored when

Hi all, I searched through the archives, but couldn't find a fix... Basically, I've got a bunch of numeric vectors and one character vector that I want to bind into a data frame. When I include the character vector as a column in the data frame, all the numeric columns get factored in the data frame, which makes it tough to call those columns for calculations later on. I've tried

On Fri, 30 Oct 2020, Pages, Herve wrote: > > On 10/29/20 23:08, Pages, Herve wrote: > ... >> >> I can think of 2 ways to move forward: >> >> 1. Keep I()'s current implementation but suppress the warning. We'll >> make the necessary adjustments to DataFrame() to repair columns supplied >> as I(<S4>) objects. Note that we would still be in

Hi there, Is that change in R-devel intentional? library(Matrix) m <- as(matrix(c(0, 1)), "sparseMatrix") isS4(m) # [1] TRUE x <- I(m) # Warning message: # In `class<-`(x, unique.default(c("AsIs", oldClass(x)))) : # Setting class(x) to multiple strings ("AsIs", "dgCMatrix", ...); result will no longer be an S4 object

Dear R developers, It would be great if you could implement the two minor code changes suggested below, which would help processing large objects in R. Jens Oehlschl?gel # Wish no. 1: let [.AsIs return the class AFTER subsetting, not the class of the original object # Wish no. 2: adjust write.csv and write.csv2 for multiple calls in chunked writing # Rationale no. 1: a couple of packages

Although the documentation is somewhat sketchy, I() can be used to create objects of class AsIs: > I("a") [1] "a" attr(,"class") [1] "AsIs" "character" > I(4) [1] 4 attr(,"class") [1] "AsIs" "numeric" > I(4 + 0i) [1] 4+0i attr(,"class") [1] "AsIs" "complex" > This

Dear All, a Surv object I put in a data frame behaves somehow unexpected (see example). If I do a Cox regression on the original Surv object it works. If I put it in a data.frame and do the regression on the data frame it does not work. Seemingly it has to do with the class attribute, because if I change the class attribute to let "Surv" appeare first, again it works. Is this known?

Hello Peter, Thank you, and the R core team, for the new release. I see that in R 2.11.0 there is now support for rendering of raster (bitmap) images through rasterImage(). I am wondering - can this be used to create a texture/fill-pattern for hist()/barplot() ? (A request made several times throughout the years on the mailing list. For example:

Hi everyone, I am interested in estimating this type of random effects panel: y_it = x'_it * beta + u_it + e_it u_it = rho * u_it-1 + d_it rho belongs to (-1, 1) where: u and e are independent and normally zero-mean distributed. d is also independently normally zero-mean distributed. So, I want random effects for group i to be correlated in t, following an AR(1) process. I am

Hi all, I believe there is an issue with passing NULL to the function I(). class(NULL) # "NULL" (as expected) print(NULL) # NULL (as expected) is.null(NULL) # TRUE (as expected) According to the documentation I() should return a copy of its input with class "AsIs" preprended: class(I(NULL)) # "AsIs" (as expected) print(I(NULL)) # list() (not expected!

Here's an example (session info at the end). > tmpv <- c('\265g/L','Bq/L') > order(tmpv) [1] 2 1 > tmpv <- I(tmpv) > order(tmpv) Error in if (xi > xj) 1L else -1L : missing value where TRUE/FALSE needed > foov <- gsub('\265','',tmpv) > order(foov) [1] 2 1 > str(tmpv) Class 'AsIs' chr [1:2] "\265g/L"

Hi, I have the following question about creating data frames. I want to create a data frame with 2 components: a vector and a matrix. Let me use a simple example: y <- rnorm(10) x <- matrix(rnorm(150), nrow=10) Now if I do dd <- data.frame(x=x, y=y) I get a data frame with 16 colums, but if, according to the documentation, I do dd <- data.frame(x=I(x), y=y) then str(dd)