当我知道某些模拟失败时，从 runjags 获取 coda 文件

如何解决当我知道某些模拟失败时，从 runjags 获取 coda 文件

我正在按模拟 ID 拆分我的数据集，并将 runjags 函数同时应用于这些子数据集的每一个。这使我能够利用并行处理并在集群上运行我的模拟。一个需要 1 天多的工作可以在大约 2 小时内完成。

在我运行的 1000 次模拟中，大约有 25 次失败。我正在使用带有陷阱捕获错误的 for 循环从成功运行的模拟中提取 coda 文件。问题是，一旦模拟失败，错误就会影响我使用的所有内核，而且我也无法提取成功运行的模拟的 coda 文件。

有什么建议吗？我在下面包含了代码和日志文件。谢谢。

library(parallel)
library(coda)

#1) using mclapply to apply a function to all simulations simultaneously

output_models <- parallel::mclapply(subsetdata,function(x){
  library(runjags)
  set.seed(1)
  model_data = x
 
  
  runJagsOut <- run.jags(method = "simple",model = "tempModel.txt",monitor = c( "mu" ),data = model_data,#inits = initsList,# NOTE: Let JAGS initialize.
                         n.chains = 1,# NOTE: Not only 1 chain.
                         adapt = 500,burnin = 3000,sample = 2500,thin = 1,summarise = TRUE,plots = FALSE)
  return(runJagsOut)
  
},mc.cores = numcores)


#2) Build an empty list vector

mcmc <- list()

#3) Extracting coda files for each of the simulations. tryCatch function in place to 'ignore' simulations that fail

for (SimulID in 1:length(unique(df$SimulID))) {
  tryCatch({
  mcmc[[SimulID]] <- cbind(output_models[[SimulID]][["mcmc"]][[1]],SimulID)
  },error=function(e){cat("ERROR :",conditionMessage(e),"\n")})
}

#4) Main text file with the coda for each simulation

lapply(mcmc,function(x) write.table( data.frame(x),'output.txt',append= T,sep=',',col.names = FALSE ))

这是我在集群上完成作业后从日志文件中看到的内容。第 1000 次模拟后出现错误，后跟 for 循环的下标越界错误。

. Initializing model
. Adapting 500
-------------------------------------------------| 500
++++++++++++++++++++++++++++++++++++++++++++++++++ 100%
Adaptation successful
. Updating 3000
-------------------------------------------------| 3000
************************************************** 100%
. . Updating 2500
-------------------------------------------------| 2500
************************************************** 100%
. . . . Updating 0
. Deleting model
. 
Simulation complete.  Reading coda files...
Coda files loaded successfully
Calculating summary statistics...
Finished running the simulation
Warning message:
In parallel::mclapply(subsetdata,function(x) { :
  scheduled cores 39,24,35,21,22,23,29,3,8,19,47,34,6,48,10,33,38,41,31,18,5,16,37 encountered errors in user code,all values of the jobs will be affected
ERROR : subscript out of bounds 
ERROR : subscript out of bounds 
ERROR : subscript out of bounds