similar to: Announce: edtdbg, integrating R's debug() with your text editor

I've developed a new R debugging tool, debugR, available at http://heather.cs.ucdavis.edu/debugR.html This basically replaces my edtdbg, which I will no longer be supporting. The new tool is now decoupled from one's text editor, and has a lot more features than edtdbg did. Try it! Feedback is encouraged, of course. Norm Matloff

A few weeks ago, I released my package edtdbg, which integrates R's debug() with your text editor. At the time, I said I'd release a version with more features in a couple of days. Well, it's taken a while, as I've experimented with various approaches, but I'm now releasing the new version, introducing the new features I had in mind then and some I've thought of since

My long-promised Rdsm package is now on CRAN. Some of you may recall that I made a prototype available on my own Web page last July. This is the official version, much evolved since I released the prototype. The CRAN description states: Provides a threads-like programming environment for R, usable both on a multicore machine and across a network of multiple machines. The package

My edtdbg debugging tool is now on CRAN, at http://cran.r-project.org/web/packages/edtdbg/index.html I've added a few new commands since the last time I announced the package here. I'll enclose command list at the end of this message. Currently the package is implemented for Vim. I have a volunteer to adapt it to Emacs, so I'm hopeful it will be usable for Emacs fans later.

As I mentioned last week, I've been developing a package that I call Rdsm ("R distributed shared memory"), modeled after a similar package, PerlDSM, I wrote for Perl some years ago. It is now in alpha form, so I'm not uploading to CRAN yet, but it is definitely usable, and I am releasing it at http://heather.cs.ucdavis.edu/~matloff/R/Rdsm I hope many try it out, and give me

Hi all, I am looking for a function similar to mclapply() that would work with GPU cores. I have looked at all possible packages related to GPU computing but they are mainly providing functionality for big dataset or big matrices. I use mainly mclapply to speed up simulations by running several simulations in parallel, which works nicely. Is it possible to do the same with a multicore GPU? I

On 2009-07-01, David M Smith <david at revolution-computing.com> wrote: > REvolution Computing has just released three new packages for R to > CRAN (under the open-source Apache 2.0 license): foreach, iterators, > and doMC. Together, they provide a simple, scalable parallel computing > framework for R that lets you take advantage of your multicore or > multiprocessor

Hi all, I have a multiple queing situation I'd like to simulate to get some idea of the distributions - waiting times and allocations etc. Does R has a package available for this - many years ago there used to be a language called "simscript" for discrete event simulation and I was wondering if R has an equivalent (or hopefully with graphics, something better!). Apologies if there

Hi All, I am attempting to simulation an inventory model on R and I am having some problems. I believe the problem is when I define my demand rate is stays constant throughout so when I do need to reorder the model does not recognise it as I have the initial supply arrival time set to infinity at the start as no order has been played but I have an if statement saying, if the level falls below a

Martin, Jim can speak directly to his motivations; I don't claim to be able to do so. That said, I suspect this is related to a conversation on twitter about wanting an infix "unquote" operator in the context of the non-standard evaluation framework Hadley Wickham and Lionel Henry (and possibly others) are working on. They're currently using !!! and !! for things related to

I have a question about reference classes, which someone here undoubtedly can answer immediately, saving me hours of wading through indecipherable internal code. :-) Thanks in advance. Reference class data is mutable, fine, but in what sense? Is it really physical, or is it just a view given to the programmer? If for instance I have vector as a field in a reference class, and I change one

I guess this would establish a separate "namespace" of symbolic prefix operators, %*% being an example in the infix case. So you could have stuff like %?%, but for non-symbolic (spelled out stuff like %foo%), it's hard to see the advantage vs. foo(x). Those examples you mention should probably be addressed (eventually) in the core language, and it looks like people are already able

On 12.09.2018 20:20, G?bor Cs?rdi wrote: > This is all normal, a fork cluster works with processes, that do not > share memory. And if you are after shared-memory parallelism, you can try the 'Rdsm' package: https://cran.r-project.org/package=Rdsm Greetings Ralf -- Ralf Stubner Senior Software Engineer / Trainer daqana GmbH Dortustra?e 48 14467 Potsdam T: +49 331 23 61 93 11 F:

I find the R debug package very useful. I've installed and used it on several of the machines I use, without problems, but on one machine I get the following error: Loading required package: mvbutils Loading required package: utils MVBUTILS: no "tasks" vector found in ROOT Loading required package: tcltk Loading Tcl/Tk interface ... done [Previously saved

I am interested in running R commands asynchronously. My first choice is in the same R session that I am currently in. Here, the goal would be to run something like RunAsynchSameSession(myfunction(), "outputname.rda") Once RunAsynchSameSession had started myfunction(), RunAsynchSameSession would complete immediately. myfunction would keep going. It is OK if execution of the

Gabe, The unary functions have the same precedence as normal SPECIALS (although the new unary forms take precedence over binary SPECIALS). So they are lower precedence than unary + and -. Yes, both of your examples are valid with this patch, here are the results and quoted forms to see the precedence. `%chr%` <- function(x) as.character(x) `%identical%` <- function(x, y)

I agree there is no reason they _need_ to be the same precedence, but I think SPECIALS are already have the proper precedence for both unary and binary calls. Namely higher than all the binary operators (except for `:`), but lower than the other unary operators. Even if we gave unary specials their own precedence I think it would end up in the same place. `%l%` <- function(x) tail(x, n =

Hello all, A friend recently brought to my attention that vector assignment actually recreates the entire vector on which the assignment is performed. So for example, the code: x[10]<- NA # The original call (short version) Is really doing this: x<- replace(x, list=10, values=NA) # The original call (long version) # assigning a whole new vector to x Which is actually doing this: x<-

Here's a basic question that doesn't seem to be completely answered in the docs, and which unfortunately I've not had time to figure out by wading through the R source code: In a vector (or array) element assignment such as z[3] <- 8 is there in actuality a full rewriting of the entire vector pointed to by z, as implied by z <- "[<-"(z,3,value=8) Assume

>After off list discussions with Jonathan Carrol and with >Michael Lawrence I think it's doable, unambiguous, >and even imo pretty intuitive for an "unquote" operator. For those of us who are not CS/Lisp mavens, what is an "unquote" operator? Can you expression quoting and unquoting in R syntax and show a few examples where is is useful, intuitive, and fits in to