similar to: foreach takes foreever?

Hello, I am trying to run a small example with foreach, but I am having some problems. Here is the code: *library(doMC) registerDoMC() zappa = list() frank = list() foreach (i = 1:4) %dopar% { zappa[[i]] = kmeans (iris[-5],4) frank[[i]] = warnings() }* The code runs without error. However the zappa and frank will be empty lists. If I use regular *for *instead, the list will be filled up

Hi Everybody, Thanks in advance for your help. This is my first time using the foreach statement and I cant get it to work properly so here is what i have test<-function(){ repeat { cand2[l-1]<-rinvgamma(1,phi,lambda[l-1]) q2<-dinvgamma(cand2[l-1],phi,lambda[l-1]) p2<-cand2[l-1]^-1.5*exp(-y[l]^2/(2*cand2[l-1]))*exp(-((log(cand2[l-1])-mu_t_cand[l-1])^2)/2*sigmasq)

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 expeRts, is it possible to carry out calculations between different foreach() calls? As for nested loops, you want to carry out calcuations not depending on the inner loop only once and not for each iteration of the innermost loop. Cheers, Marius library(foreach) foreach(i=1:3) %:% foreach(j=1:2) %do% { i <- i+1 print(paste(i,j)) } foreach(i=1:3) %:% i

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

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

I took a look at Hadley's lubridate which seems a very neat package, but i am having a small problem with  concatenating lubridates to build vectors of it. Namely when function c( )  is applied to lubridate seems to change time to a local timezone in this particular case changing the date to previous one.  > d<-ymd('20111231') > d [1] "2011-12-31 UTC" > c(d) [1]

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,

Hi all, I would like to parallelize some R code and would like to use the 'foreach' package with a foreach loop. However, whenever I call a function from an enabled package outside of MASS, I get an error message that a number of the functions aren't recognized (even though the functions should be defined). For example: library(foreach) library(doSMP) library(survival) # Create the

Hi! I'm a recent convert from Stata, so forgive my ignorance. In Stata, I can write foreach loops (example below) foreach var of varlist p1-p14 { foreach y of varlist p15-p269 { reg `var' `y' } } It's looping p1-p15, p1-p16...., p1-p269, p2-p15, p2-p16,... p2-p269,... variable pairs. How can I write something similar in R? I 'tried' understanding the

Hello, I'm running some code that requires untaring many files in the first step. This takes a lot of time and I'd like to do this in parallel, if possible. If it's the disk reading speed that is the bottleneck I guess I should not expect an improvement, but perhaps it's the processor. So I want to try this out. I'm working on windows 7 with R 2.15.1 and the latest foreach

Hi there! I have become a big fan of the 'foreach' package allowing me to do a lot of stuff in parallel. For example, evaluating the function f on all elements in a vector x is easily accomplished: foreach(i=1:length(x),.combine=c) %dopar% f(x[i]) Here the .combine=c option tells foreach to combine output using the c()-function. That is, to return it as a vector. Today I discovered the

Hi, just during these vacation days, I'm trying to approach with multicore package and I have some troubles with foreach. ex. foreach(.combine=c, ii=1:200, jj=1:500) %dopar% makefunction[ii,jj] Command seem to work but if I see ii and jj value at the and of cycle, they are both 200 instead than ii=200 and jj=500. Why?? Can someone help me? Thank you in advance. Max -- View this

I'm trying to find examples of the foreach pattern being used in tablegen files. The problem I am trying to solve is to simplify the amount of tablegen code I have to produce because each operand of an instruction can be a register or a literal. So for binary, we have 4 instructions, ternary, 8, and quaternary 16 combinations. Instead of writing all the combinations out, I'd like to use

Hi all, Sometimes I'll find myself "ctrl-c"-ing like a madman to kill some code that's parallelized via foreach/doMC when I realized that I just set my cpu off to do something boneheaded, and it will keep doing that thing for a while. In these situations, since I interrupted its normal execution, foreach/doMC doesn't "clean up" after itself by killing the

I think a multiclass may be a better fit for what you are trying to do. In fact, this is the canonical example for multiclasses: <http://llvm.org/docs/TableGenFundamentals.html#multiclass-definitions-and-instances>. --Sean Silva On Mon, Aug 6, 2012 at 1:55 PM, Villmow, Micah <Micah.Villmow at amd.com> wrote: > I’m trying to find examples of the foreach pattern being used in

Hi list, My attention was drawn to the foreach package by recent posts...I decided to have a look... I'm using R.2.9.1 on Windows, I have downloaded the foreach package today (v 1.2.1), together with iterators (v. 1.0.1) and codetools (v.0.2-2). Full of hope I try the most simple thing of all out of the package vignette : > x <- foreach(i = 1:3) %do% sqrt(i) and get : > Erreur

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",

I recently learned about the bigmemory and foreach packages and am trying to use them to help me create a very large matrix. Without those packages, I can create the type of matrix that I want with 10 columns and 5e6 rows. I would like to be able to scale up to 5e9 rows, or more, if possible. I have created a simplified example of what I'm trying to do, below. The first part of the

That is what I currently have, I'm trying to simplify them even further since my multiclass file is enormous because of the amount of combinations. I have things like this: multiclass instmcRegImm<...> { def rr: inst<...>; def ri: inst<...>; def ir: inst<...>; def ii: inst<...>; } multiclass instmc<...> { defm i8 : instmcRegImm<...>; ^-- repeat for 15