similar to: Using Foreach for downloading data

I have this code which is working library("checkpoint") library("gtrendsR") library("doParallel") cl<-makeCluster(4) registerDoParallel(cl) gconnect(usr = "email at gmail.com", psw = "password", verbose = FALSE) names <- c("apple","shit", "android", "rocks") formula <- function(x){ x0 <-

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

Some might have noticed that REvolution Computing released the doSMP package to the general public about a month and a half ago, which allows multiple cores to be accessed for parallel computation in R. Some of our physical habitat calculations were taking an extraordinary amount of time to complete and required over-weekend runs, which prompted our interest in this package. What follows

Hi, I am trying to parallel computing with foreach function, but not able to get the result. I know that in parallel processing, all result is collected in list format, but I am not able to get input there. Any help is really appreciated. esf.m <-foreach (i = 1:n.s, .combine=rbind) %dopar% { EV <- as.data.frame(eig$vectors[,1:n.candid[i]]) colnames(EV) <- paste("EV",

Hello Mikis: Thanks a lot, it worked. Could you tell me what the problem was? Regards, Nik ----- Original Message ----- From: r-help-request at r-project.org To: "r-help" Sent: Sunday, March 11, 2018 6:00:02 AM Subject: R-help Digest, Vol 181, Issue 11 Send R-help mailing list submissions to r-help at r-project.org To subscribe or unsubscribe via the World Wide Web, visit

Whas missing the R in the command line: "mpirun -n --hostfile /home/hostfile R --no-save -f rtest.R" Hope this helps mario On 13-Jan-11 22:08, Justin Moriarty wrote: > Hi, > Just wanted to share a working example of doSNOW and foreach for an openMPI cluster. The function eddcmp() is just an example and returns some inocuous warnings. The

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.

Dear Nik Try the following code loo_predict.mu <- function(model.obj, input.data) { yhat <- foreach(i = 1 : nrow(input.data), .packages="gamlss", .combine = rbind) %dopar% { updated.model.obj <- update(model.obj, data = input.data[-i, ]) predict(updated.model.obj, what = "mu", data = input.data[-i, ], newdata = input.data[i,], type =

Dear all, I am converting a large process to a parallel backhend using doMC and foreach. Basically, I havea long list of input graph files and each of them calls soem basic igraph package functions. I am parallelizing the run, in order to save time. All works fine, and each %dopar% call ends with a vector of results that at the end got fed into a data frame and saved as a csv table. When I

R programming question, not machine learning, although that's the content. Apologies to all for whom the following code is eye-burning. I am using foreach() to run a simulation on a randomForest model (actually conditional randomForest ... "party" package). The simulation is in two dimensions. examining how "mtry" and "ntrees" are related in terms of predictive

Dear All, I have three classes of questions about generating random numbers with different packages (windows xp 32bit R). . 1. Suppose I would like to use package *foreach*, can I use current Sys.time as a seed? Although I can get the time up to1e-6 second precesion, the code below dose not work well on a local machine with two cores. ################# library(foreach) library(snow)

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 all, Just wondering if someone could help me out converting my code from a for() loop into a foreach() loop or using one of the apply() function. I have a very large dataset and so I'm hoping to make use of a parallel backend to speed up the processing time. I'm having trouble getting selecting three variables in the dataset to use in the foreach() loops. My for() loop code is:

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

Dear R-List member, I have a problem when I'm trying to save two arrays from a foreach-loop. I'm also not sure whether this is possible or just my inexperience. However, this works perferctly fine with a for-loop. Here is an example code - any help is much appreciated!!: ############ n.vpn = 2 n.run= 3 # create to empty matrices sme = matrix(NA,4,n.vpn) test = matrix(NA,4,n.vpn) #

I know this is not a revolution support forum, but as anyone noticed the following? I have a foreach loop to generate random samples. If I run the exact code below in normal r (2.14.1) it works as expected, but if I run it from revolution 4.2.0 each loop returns the same numbers. The only way I can get revolution to give different numbers is using 1 instead of 8 in registerDoSNOW(makeCluster(8,

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

Hi all, Within a foreach loop with doSNOW, we cant call functions which come from the non-default package. We need to load(require/library) the package once more within the foreach loop. Anyone knows why would happen like this? Is it caused by the snow package and something happened when "snow" parallelize the job? Other than load the package once more with in the foreach loop, is

Dear R-List member, tried implement the foreach loop. It works fine, when I'm using %do%, but not when I'm using %dopar%. I always receive one of the following error messages: error in { : task 1 failed - "Objekt 'S3' not found" - could the .export be an solution for this?? Any help is much appreciated! The Code hast the following structure: ########## dft3 =