[R] Package gamlss used inside foreach() and %dopar% fails to find an object

[Nik Tuzov]

Hello Jeff:

Thanks for replying.
I made a mistake in my original post.
The same error is generated with %do% as well, so it seems to be gamlss-related.

Nik


----- Original Message -----
From: "Jeff Newmiller" <jdnewmil at dcn.davis.ca.us>
To: "r-help" <r-help at r-project.org>, "Nik Tuzov" <ntuzov at beacon.partek.com>
Sent: Friday, March 9, 2018 11:16:21 AM
Subject: Re: [R] Package gamlss used inside foreach() and %dopar% fails to find an object

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.

On March 9, 2018 7:50:44 AM PST, Nik Tuzov <ntuzov at beacon.partek.com> wrote:
>
>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
>
># --------------------------------------------------------------
>
>library('gamlss')
>library('foreach')
>library('doParallel')
>
>registerDoParallel(cores = 4)
># Generate data
>set.seed(314)
>sample.size <- 30
>input.processed.cut <- data.frame(TP = round(runif(sample.size) * 100),
>
>                                 FP = round(runif(sample.size) * 100), 
>                                  x = runif(sample.size))
># Fit Beta-binomial
>model3 <- gamlss(formula = cbind(TP, FP) ~ x,   
>                 family = BB,  
>                 data = input.processed.cut) 
>
># Get the leave-one-out values
>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", newdata = input.data[i,], type
>= "response")
>  }
>  return(data.frame(result = yhat[, 1], row.names = NULL))
>}
>
>par.run <- loo_predict.mu(model3, input.processed.cut)
>
># Error in { : task 1 failed - "object 'input.data' not found" 
>
>#
>------------------------------------------------------------------------
>
>> version
>               _                           
>platform       x86_64-w64-mingw32          
>arch           x86_64                      
>os             mingw32                     
>system         x86_64, mingw32             
>status                                     
>major          3                           
>minor          4.3                         
>year           2017                        
>month          11                          
>day            30                          
>svn rev        73796                       
>language       R                           
>version.string R version 3.4.3 (2017-11-30)
>nickname       Kite-Eating Tree
>
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