similar to: Is there a place to put executable R scripts in new packages?

Dear R users, I have a matrix composed of lists: m <- matrix( list(), nrow=1, ncol=3 ) m[[ 1, 1 ]] <- list("A", "B") m[[ 1, 2 ]] <- list("A", "C") m[[ 1, 3 ]] <- list("A", "B") and want to get the sub-matrix where cells contain "B". But m[ , "B" %in% m[ 1, ], drop=F ] as well as m[ , "B"

Dear R experts, recently I tried to debug a R function with an internal lapply call. When debugging I seem not to be able to use the "n" command to debug the inner function called by lapply. How could I achieve this? *For example:* test <- function( ) { lapply( 1:3, function( x ) x + 1 ) } debug( test ) *Start debug:* > test() debugging in: test() debug bei #1:{

Dear R experts, I hope everyone has had a happy easter break. Recently my work included writing R function that need to call external tools. I did this using R's system function for example: system( paste( 'tool', '-input', path_to_input, '-output', path_to_output, '-other_switch', some_val ) ) I have two question about this: 1) Is there a way to implement

Dear parallel users and developers, I might have encountered a bug in the function 'mclapply' of package 'parallel'. I construct a matrix using the same input data and code with a single difference: Once I use mclapply and the other time lapply. Shockingly the result is NOT the same. To evaluate please unpack the attached archive and execute Rscript mclapply_test.R I put the

Dear R experts, since more or less half a year I am using R. In many of my computations I construct huge matrices. Often I do so using 'cbind' on named lists: do.call( 'cbind', list( "Column_A"=list("Row_one"=1.0, "Row_two"=2.0, "Row_three"=3.0), "Column_B"=list("Row_one"=4.0, "Row_two"=5.0,

Dear R community, I have a medium sized matrix stored in variable "t" and a simple function " countRows" (see below) to count the number of rows in which a selected column "C" matches a given value. If I count all rows matching all pairwise distinct values in the column "C" and sum these counts up, I get the number or rows of "t". If I delete the

Dear R experts, recently I started developing a Rcpp package "OpenMPTest". Within that package I want to use OpenMP, as in the following code example: // header file #include <omp.h> using namespace Rcpp ; RcppExport SEXP testOpenMP( SEXP nThreads ) ; // cpp file SEXP testOpenMP( SEXP nThreads ) { BEGIN_RCPP NumericVector numberThreads = NumericVector( nThreads );

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

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

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",

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 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?

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". >

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

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,

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)

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"

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