R中的内存问题“错误：无法分配大小为344 kb的向量”

Question

我的memory.limit() 是 3583，我家里有一台 8G 内存的 64 位机器，只是在办公室远程访问我的电脑然后发现它也是 8G 内存。所以 我无法成功运行下面的R代码，我应该重置内存限制吗？但是有人认为这是一种危险的方法，谁能告诉我如何解决这个问题？提前致谢！

loop<-1000;T<-45
bbb<-list()
for(i in 1:loop)
{
  bbb[[i]]<-list()
  bbb[[i]][[1]]<-matrix(rep(1,loop*(T-1)),loop,T-1)
  bbb[[i]][[2]]<-matrix(rep(0,loop*(T-1)),loop,T-1) 
  bbb[[i]][[3]]<-matrix(rep(0,loop*(T-1)),loop,T-1) 
  bbb[[i]][[4]]<-matrix(rep(0,loop*(T-1)),loop,T-1) 
  bbb[[i]][[5]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[6]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[7]]<-matrix(rep(0,loop*(T-1)),loop,T-1) 
  bbb[[i]][[8]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[9]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[10]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[11]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[12]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[13]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[14]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[15]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[16]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[17]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[18]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[19]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[20]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[21]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[22]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[23]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[24]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[25]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[26]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[27]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[28]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[29]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[30]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[31]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[32]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
  bbb[[i]][[33]]<-matrix(rep(0,loop*(T-1)),loop,T-1)
}

Answer 1

我想这取决于你对矩阵列表做了什么，但也许你可以把你的任务分成更小的块？或者您可以尝试使用lapply，它在我的机器上运行得更快，但最终会创建一个大小完全相同的对象。我认为 lapply 在重复数据时有一些节省内存的优势。

如果这不起作用，请尝试查看 Matrix 包和稀疏矩阵。

create_bbb <- function(loop = 1000, T = 45){

  inner.list <- lapply(1:33, FUN = function(x){

    if(x == 1) fill <- 1
    else fill <- 0

    return(matrix(rep(fill, loop * (T-1)), loop, T-1))

  })

  bbb <- lapply(1:loop, function(.) inner.list)

  return(bbb)
}


bbb_test <- create_bbb()

# Check
all.equal(bbb, bbb_test)
# TRUE