无法重组 R 中嵌套 foreach 循环的结果

Unable to reorganize results of nested foreach loop in R

代码(我目前所用的更简单的版本)运行与串行后端完美结合:

regis <-list()
EOFvalues <-array(,c(5,6))
EOFvaluesM <-array(,c(5,6))

 for(j in 1:6) {
  for(k in 1:5){
    loc_no <- (j-1)+k
    regis[[j]]=c(j,k)
    EOFvalues[k,j]=j+k
    EOFvaluesM[k,j]=j*k
}}

结果为 1:regis(列表):

2:EOFvalues(一个数组):

3:EOFvaluesM(一个数组):


但是一旦我运行它使用并行后端

regis <-list()
EOFvalues <-array(,c(5,6))
EOFvaluesM <-array(,c(5,6))

library(doParallel)
cores0=detectCores()
cl<-makeCluster(cores0, type= "SOCK" ,outfile="")
registerDoParallel(cl)

oper <- foreach(j=1:6, .combine='c',.export = c("%dopar%"),  .packages = c("doParallel")) %dopar% {
  foreach(k=1:5,.export = c("%dopar%"),  .packages = c("doParallel")) %do% {
                  regis[[j]]=c(j,k)
                  EOFvalues[k,j]=j+k
                  EOFvaluesM[k,j]=j*k
                  par_res <- list(regis,EOFvalues,EOFvaluesM)
                }

}
stopImplicitCluster()`

所有的结果都很混乱:

(我的意思是我没有得到串行后端给出的结果,这可能是因为我对 R 中的并行性知之甚少)。

我需要获得类似的结果,以便在我的项目中进一步进行并节省内存和时间(因为实际上,EOFvalues 和 EOFvaluesM 的顺序为 (324,625))。所以,我不能离开并行后端。是否可以使用此代码重新生成相同的结果?如果是,那又如何?

幸运的是,我有一个看起来简单的解决方案来解决我的问题。

regis <-list()
EOFvalues <-array(,c(5,6))
EOFvaluesM <-array(,c(5,6))

library(doParallel)
cores0=detectCores()
cl<-makeCluster(cores0, type= "SOCK" ,outfile="")
registerDoParallel(cl)

oper_a <- foreach(j=1:6, .combine='rbind',.export = c("%dopar%"),  .packages = c("doParallel")) %dopar% {
  foreach(k=1:5,.export = c("%dopar%"),  .packages = c("doParallel")) %do% {
                  res<-list()
                  res$regis <- c(j,k)
                  res$EOFvalues <- j+k
                  res$EOFvaluesM <- j*k
                  return(res)
                  # regis[[j]]=c(j,k)
                  # EOFvalues[k,j]=j+k
                  # EOFvaluesM[k,j]=j*k
                  # par_res <- list(regis,EOFvalues,EOFvaluesM)
                }

}
################### The Solution ################
final_regis <- list()              #made a list for all the three parameters
final_EOFvalues <- list()         #...so that EOFvalues and EOFvaluesM can be converted from list to matrix
final_EOFvaluesM <- list()

for(i in 1:length(oper_a)){  #Here the above made lists are filled
  final_regis <- c(final_regis,oper_a[[i]][["regis"]])
  final_EOFvalues <- c(final_EOFvalues,oper_a[[i]][["EOFvalues"]])
  final_EOFvaluesM <- c(final_EOFvaluesM,oper_a[[i]][["EOFvaluesM"]])
}
#Unlist to convert them into vectors.Also i don't know why but as.matrix doesn't give the correct dimensions.So I used simply matrix 
mat_Afinal_EOFvalues <- matrix(unlist(final_EOFvalues),nrow=5,byrow=TRUE)
mat_Bfinal_EOFvaluesM <- matrix(unlist(final_EOFvaluesM),nrow=5,ncol=6,byrow=TRUE)
stopImplicitCluster()
#Hurray