similar to: How setClass() may introduce a binary dependency between packages

Hello R-devel, Since Pavel has mentioned ABI-level dependencies between packages [1], it may be relevant to revisit the related problem mentioned ~1.5 years ago by Dirk [2]. While the current version of SeuratObject doesn't exhibit this problem, a combination of package versions described by Dirk still breaks each other on R-devel: 1. Install Matrix_1.5-1 2. Install SeuratObject_4.1.3 from

CRAN, by relying on the powerful package management system that is part of R, provides an unparalleled framework for extending R with nearly 20k packages. We recently encountered an issue that highlights a missing element in the otherwise outstanding package management system. So we would like to start a discussion about enhancing its feature set. As shown below, a mechanism to force

Hello R developers, Platform: Windows 2000. Compiler: GNU GCC - 2.95.2 (CRTDLL) I have a C function for evaluating commands using eval(SEXP,SEXP) which is included in a personal make of R.dll. (Similiar to R_Proxy_evaluate() in rproxy_impl.c) Using SETJMP to catch errors works but there is a problem. For example, the following code: if (SETJMP(R_ToplevelContext->cjmpbuf)) //

Hello, (This is follow up from this thread: http://www.nabble.com/execution-time-of-.packages-td22304833.html but with a different focus) I am often confused by the result of the profiler, when a loop is involved. Consider these two scripts: script1: Rprof( ) x <- numeric( ) for( i in 1:10000){ x <- c( x, rnorm(10) ) } Rprof( NULL ) print( summaryRprof( ) ) script2:

I'm having difficulty with Rprof. I have a documentation example test.qss that runs fine without profiling, but under Rprof, > Rprof() > source("test.qss") Error in standardGeneric("model.matrix") : UseMethod used in an inappropriate fashion Luke wrote about a similar circumstance last summer: # From: Luke Tierney (luke@stat.umn.edu) # Date: Fri Jul

Hi Consider the following example: f <- function(expr) g(expr) g <- function(expr) { ? h(expr) } h <- function(expr) { ? expr # evaluation happens here ? i(expr) } i <- function(expr) { ? expr # already evaluated, no costs here ? invisible() } rprof <- tempfile() Rprof(rprof) f(replicate(1e2, sample.int(1e4))) Rprof(NULL) cat(readLines(rprof), sep = "\n") #>

I'm picking up this 5-year old thread. 1. About the four memory allocations without a stacktrace I think the four memory allocations without a stacktrace reported by Rprofmem(): > Rprofmem(); x <- raw(2000); Rprofmem("") > cat(readLines("Rprofmem.out", n=5, warn=FALSE), sep="\n") 192 :360 :360 :1064 :2040 :"raw" are due to some

Hi Martin, package arules heavily relies on ngCMatrix and uses multiplication and addition for logical operations. I think it makes sense that in a mixed operation with one dgCMatrix and one ngCMatrix the ngCMatrix should be "promoted" to a dgCMatrix. The current behavior of %*% and friends is in deed confusing: > m <- matrix(sample(c(0,1), 5*5, replace=TRUE), nrow=5) >

On 23/04/2018 6:33 AM, Peter Simons wrote: > Hi, > > I just tried to upgrade Nixpkgs to R 3.5.0, but unfortunately the new > version fails its regression test suite. We configure the build using > the flags "--without-recommended-packages", in case that's relevant. You > can see a complete build log with all relevant information at [1]. > Anyway, the test

Hi, I think this is a bug (even though I can't find documentation explicitly saying that it should work). Basically, Rf_PrintValue(obj) fails when 'obj' is an S4 object that should be printed using show() rather than print(). From the error message I'm guessing that the need to use show is detected correctly but then show is not found. "cbind2" in the code below is just

I'm very green with R, so maybe this is not a bug, but it looks like one to me. The following program segfaults at the second call to Rf_PrintValue(). To failure depends on the value of the y-string. E.g., if I change it from "coverage" to, say, "COVERAGE", the segfault does not occur. /* bug.c */ #include <stdio.h> #include <Rinternals.h> #include

Hi The following attempt to minimize memory consumption fails. m1 <- Matrix(c(rep(1,1000), rep(0,2000)), 1500) m2 <- as(m1, "ngCMatrix") Then m1 %*% c(1,2) produces the desired matrix product, while m2 %*% c(1,2) results in the error Error in x %*% y : Cholmod error 'invalid xtype' at file:../MatrixOps/cholmod_sdmult.c, line 82 I might be making a wrong

Hi Martin I got stung by this last week. glmnet produces a coefficient matrix of class ?dgCMatrix? If a predictor matrix was created using sparseMatrix as follows, one gets unexpected results, as this simple example shows. My fix was easy (I always convert the predictor matrix to class ?dgCMatrix? now) Trevor > y=Matrix(diag(4)) > y 4 x 4 diagonal matrix of class "ddiMatrix"

Hi, I just tried to upgrade Nixpkgs to R 3.5.0, but unfortunately the new version fails its regression test suite. We configure the build using the flags "--without-recommended-packages", in case that's relevant. You can see a complete build log with all relevant information at [1]. Anyway, the test failures look like this: | make[3]: Entering directory

I am new to R( but quickly being awed by the range of this it can accomplish, you have one more convert to the useR universe). I have successfully implemented the apriori function and are getting great results. My question concerns how to export these results. I have read lots about write.csv functions and exporting data frames and other standard objects. Im having difficulty working with these S4

Hi I think I have asked these questions earlier, but I been able to find answers from the documentation (which I found poorly written in several places). Will someone be kind enough to give me answers and enlighten me? (as in explain with CODE?) I want to embed R in my application and use the fPortfolio package for carrying out risk management computations. Right now I'm reading the Rmetrics

The Rprofmem facility is currently enabled only if the configuration option --enable-memory-profiling is used. However, the overhead of having it enabled is negligible when profiling is not actually being done, and can easily be made even smaller. So I think it ought to be enabled all the time. I've attached a patch doing this, which also makes a number of other improvements to Rprofmem,

I'm trying to learn about R's PROTECT system. To that end I've tried to create an example of C code that doesn't protect anything. I was hoping it would either segfault from trying to access deallocated memory, or maybe print out nonsense results because the unprotected memory got overwritten, but I can't make either happen. Here's my current code (all in R, using the

Full_Name: Jelle Goeman Version: 1.9.0 OS: mingw32, windows 2000 Submission from: (NULL) (145.88.209.33) Hi Everyone, I get very strange results using the function hasArg with the ... function argument. In my own function: > gt <- globaltest(X,Y) > sampling(gt) works fine, but > sampling(globaltest(X,Y)) results in: Error in eval(expr, envir, enclos) : "missing"

I am having some difficulties using dynamically loaded C functions on a Sparc 10 with R compiled using cc (both R-0.49 and R-0.50). I get sporadic errors with the error message: Error: character variables must be duplicated in .C/.Fortran, with C functions which pass character variables. my C functions look like: anyfunc(char **filename, other variables ) This error message appears about 25%