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I'm sorry, I forgot to mention that the function that has the above mentioned code was wrapped inside a foreach().
Commented Feb 26, 2015 on Monitoring progress of a foreach parallel job at Revolutions
Monitoring progress of a foreach parallel job
by Andrie de Vries R has strong support for parallel programming, both in base R and additional CRAN packages. For example, we have previously written about foreach and parallel programming in the articles Tutorial: Parallel programming with foreach and Intro to Parallel Random Number Generation...
It's a windows only solution, and it's basically the same task as StephenL described. I just added a "bar" argument to my overarching function so i could decide if I wanted to monitor the bars or not (yes for testing on my machine, no for submitting on a cluster)
if(bar==TRUE){
pb <- winProgressBar(title = "Initializing",
min = 0,max = L, width = 300)}
for (l in 1:L){
... stuff...
if(bar==TRUE){
setWinProgressBar(pb, l,
title=paste(mod, " Iteration:", round(l/L*100, 0),
"% done"))}
if(bar==TRUE){close(pb)}
Commented Feb 26, 2015 on Monitoring progress of a foreach parallel job at Revolutions
Monitoring progress of a foreach parallel job
by Andrie de Vries R has strong support for parallel programming, both in base R and additional CRAN packages. For example, we have previously written about foreach and parallel programming in the articles Tutorial: Parallel programming with foreach and Intro to Parallel Random Number Generation...
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