similar to: Submit a package which use doParallel

On 05/03/2015 6:16 PM, Brian G. Peterson wrote: > On Thu, 2015-03-05 at 18:03 -0500, Etienne Lord wrote: >> Hi, >> >> I'm trying to submit my first package which depends on doParallel: >> >> Depends: R (>= 3.0), igraph, doParallel > > add foreach to your Depends. That should resolve the error you're > seeing. Please don't do that. Use

Thanks for the quick reply. Adding all the dependencies of doParallel (foreach, parallel, iterators) in the DESCRIPTION and in import statements in NAMESPACE resolved the build_win problems. Don't know why this is required for Windows build. Thanks again. 2015-03-05 18:22 GMT-05:00 Duncan Murdoch <murdoch.duncan at gmail.com>: > On 05/03/2015 6:16 PM, Brian G. Peterson wrote: >

Buenas, Quiero ver si he paralelizado correctamente el proceso. Tengo dos dataframes, A y B y quiero calcular la distancia euclídea de todas las filas de A sobre todas las filas de B. Para ello he hecho lo siguiente #cargo las librerias library(foreach) library(doParallel) #establezco el numero de clusters, en mi caso 4, ya que el procesador tiene 4 nucleos cl<-makeCluster(4)

Dear R helpers, I have what another member on this forum described as an embarrassingly parallel problem. I am trying to fit models on subsets of some data based on unique combinations of two id factors in the dataset. Total number of combinations is 30^5, and this takes a long time. So, I would like fit models for each of the datasets produced by subsetting on the unique combinations, splitting

Hello all: Please help me with this "can't find object" issue. I'm trying to get leave-one-out predicted values for Beta-binomial regression. It may be the gamlss issue because the code seems to work when %do% is used. I have searched for similar issues, but haven't managed to figure it out. This is on Windows 10 platform. Thanks in advance, Nik #

Dear R-SIG-Debian, I am using R version 3.1.2 with rstudio-server 0.98.113 on debian build 3.2.0-4-amd64 #1 SMP Debian 3.2.68-1+deb7u1 x86_64 GNU/Linux. I often use the %dopar% operator in from the foreach package to run code in parallel. However, the only other use on the box seemingly installed a few items and suddenly %dopar% will use far more than the number of cores I am specifying and

If the code you are running in parallel is complicated, maybe foreach is not sophisticated enough to find all the variables you refer to. Maybe use parallel::clusterExport yourself? But be a aware that passing parameters is much safer than directly accessing globals in parallel processing, so this might just be your warning to not do that anyway. -- Sent from my phone. Please excuse my brevity.

Hi, all-- I've been working on a doParallel package to provide a foreach parallel backend for the new parallel package, but I am having trouble building the vignette. On my system, if I use the following minimal vignette (call it buggyVignette.Rnw): \documentclass[a4paper]{article} \title{Sweave Example 1} \author{Rich Calaway} \begin{document} \maketitle In this example

I am using 32-bit R 3.1.2 on Windows 7. I recently conducted an `R CMD check --as-cran` on a recently-developed package and received only the 'New submission' note. Research on StackOverflow and on R-devel suggested this could be ignored. I also used devtools::build_win() and received no notes or warnings, other than the one mentioned previously. Lastly, I conducted an `R CMD check` with

Hello: Could you please suggest the best way to become an "advanced" R programmer. I went through "R for dummies" by de Vries and Meys and I can see two ways to proceed: 1) Get a more advanced textbook. E.g. could you recommend Gentleman, "R for Bioinformatics"? 2) Because textbooks are limited and become obsolete fast, I can focus on learning state-of-the-art

I'm working on an update for my CRAN package "spatial.tools" and I noticed a new warning when running R CMD CHECK --as-cran: * checking CRAN incoming feasibility ... NOTE Maintainer: 'Jonathan Asher Greenberg <spatial-tools@estarcion.net>' Depends: includes the non-default packages: 'sp' 'raster' 'rgdal' 'mmap' 'abind'

See Hadley's advanced R along Thomas Mailund's books. I haven't gone through them carefully but they both seem (from what I've looked at ) to be the best ones for that. Mentions of others are appreciated. On Tue, Mar 13, 2018 at 5:26 PM, Nik Tuzov <ntuzov at beacon.partek.com> wrote: > > Hello: > > Could you please suggest the best way to become an

Hello, I have been having issues using parallel::mclapply in a memory-efficient way and would like some guidance. I am using a 40 core machine with 96 GB of RAM. I've tried to run mclapply with 20, 30, and 40 mc.cores and it has practically brought the machine to a standstill each time to the point where I do a hard reset. When running mclapply with 10 mc.cores, I can see that each process

Hi guys, I was wondering why this piece of code doesn't work: foreach (i = c(1.25,1.50)) %dopar% { assign(paste("test_",i,sep=""),i) } but, this does: foreach (i = c(1.25,1.50)) %do% { assign(paste("test_",i,sep=""),i) } Obviously, the difference is %dopar% vs. %do%. If I use %do%, I get objects test_1.25 and test_1.50, but I don't get these

Oh, I completely missed that one. It's very neat as it seems to work both on Windows and Unix. Thanks! Xavier On 10/02/15 10:52, Martyn Plummer wrote: > The CRAN package snow is superseded by the parallel package which is > distributed with R since version 2.14.0. Here are the release notes > > \item There is a new package \pkg{parallel}. > > It incorporates (slightly

Hi everyone, I'm working on a script trying to use foreach %dopar% but without success, so I manage to run the code with foreach %do% and looks like this: The code is part of a MCMC model for projects valuation, returning the most important results (VPN, TIR, EVA, etc.) of the simulation. foreach (simx = NsimT, .combine=cbind, .inorder=FALSE, .verbose=TRUE) %do% { MCPVMPA = MCVAMPA[simx]

All, I am not understanding the scoping used in foreach when it is used inside a function. I keep getting "could not find function" errors for functions that are in memory when I try to use foreach within a function call. I have a simple example below. "testFun" is in memory and works when called by foreach directly, but when I place foreach in a function called

Hi useRs, I am running a foreach loop and hoped to get a small message when it hits a multiple of 1000, but it does not work. p <- foreach(i=1:10000, .combine='c') %dopar% { if(i%%1000==0) print(i) sqrt(i) } What is the proper way to do it. Thanks everybody. Stephen B [[alternative HTML version deleted]]

I am experimenting with parallel processing using foreach and seem to be missing something fundamental. Cool stuff. I've gone through the list and seen a couple of closely related issues, but nothing I've tried seems to work. I know that the results from foreach are combined, but what if there is more than one variable within the loop? Below is a snippet (non-functioning) of code that I

I am trying to do parallel programming and I tried this library(doSNOW) library(foreach) testfunc<-function(x){ x<-x+1 x } noc<-2 cl <- makeCluster(do.call(rbind,rep(list("localhost"),noc)), type = "SOCK") registerDoSNOW(cl) clusterExport(cl=cl,c("testfunc.r")) testl<-foreach(pp=1:2) %dopar% { testfunc(pp) } And this works but if I try to