在R中使用复杂功能的tryCatch和plyr

问题描述

我有一个复杂的，很长的功能，我用来做模拟。它可以产生错误，主要是与以零方差相等的值结尾的随机向量进行比较，将其加入到PCA或逻辑回归中。

我正在使用 doMC 和 plyr 。我不想要 tryCatch 函数内的每个小东西，因为错误的可能性很多，而且每个都有很小的可能性。

如何tryCatch每个运行，而不是 tryCatch 每一行？代码是这样的：

  iteration = function（）{
a真的很长的模拟功能，可能会发生错误
} 
 reps = 10000 
 results = llply（1：reps，function（idx）{out< -iteration（）} ,. parallel = TRUE）
 
   
  foreach 包使得这比使用 plyr  
 库更容易（foreach）
 output<  -  foreach（i = 1：reps，.errorhandling ='remove'）％dopar％{
 function 
} 
  
 
 
解决方案
您可以将try catch循环包装到您传递给llply的函数中吗？
  results = llply（1：reps，function（idx）{
 out = NA 
 try（{
 out< ; -iteration（）
}，silent = T）
 out 
} ,. parallel = TRUE）
  
 
I've got a complicated, long function that I'm using to do simulations.  It can generate errors, mostly having to do with random vectors ending up with equal values with zero-variance, getting fed either into PCA's or logistic regressions.  
I'm executing it on a cluster using doMC and plyr.  I don't want to tryCatch every little thing inside of the function, because the possibilities for errors are many and the probabilities of each of them are small.
How do I tryCatch each run, rather than tryCatching every little line??  The code is something like this:
iteration = function(){
    a really long simulation function where errors can happen
    }
reps = 10000
results = llply(1:reps, function(idx){out<-iteration()},.parallel=TRUE)
EDIT about a year later:The foreach package makes this substantially easier than it is with plyr
library(foreach)
output <- foreach(i=1:reps, .errorhandling = 'remove')%dopar%{
  function
}
 解决方案 
Can you wrap the try catch loop in the function you pass to llply?
results = llply(1:reps, function(idx){
    out = NA
    try({
        out<-iteration()
    }, silent=T)
    out
},.parallel=TRUE)
                        
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