更快的方式子集数据表，而不是for循环R

我有一个数据表（您将需要安装的数据表包）在R中生成X和Y坐标和来自正态分布和均匀分布的随机数据值。坐标表示2000×1600阵列上的点，并且必须被分成16个较小的扇区，每个扇区500×400。这些扇区需要它们的正态分布值的平均值除以均匀分布值的min ^ 2。我还使用提供的函数startstop创建了两个变量x和y，它们具有16个扇区的坐标以及计算每个扇区的数字的函数。

I have a data table (you'll need the data table package installed) in R generated with X and Y coordinates and random data values from both normal and uniform distributions. The coordinates represent points on a 2000x1600 array and has to be divided into 16 smaller "sectors" each 500x400. These sectors need their mean of Normal Distribution values taken, divided by the min^2 of the Uniform Distribution values. I also created two variables x and y using a provided function startstop, that have the coordinates for the 16 sectors and a function that calculates the numbers for each sector.

library(data.table)
DT <- data.table(X = rep(1:2000, times = 1600), Y = rep(1:1600, each = 2000), Norm =rnorm(1600*2000), Unif = runif(1600*2000))

sectorCalc <- function(x,y,DT) {
    sector <- numeric(length = 16)
    for (i in 1:length(sector)) {
        sect <- DT[X %between% c(x[[1]][i],x[[2]][i]) & Y %between% c(y[[1]][i],y[[2]][i])]
        sector[i] <- sCalc(sect)
    }
    return(sector)
 }

startstop <- function(width, y = FALSE) {
    startend <- width - (width/4 - 1)
    start <- round(seq(0, startend, length.out = 4))
    stop <- round(seq(width/4, width, length.out = 4))
    if  (length(c(start,stop)[anyDuplicated(c(start,stop))]) != 0) {
        dup <- anyDuplicated(c(start,stop))
        stop[which(stop == c(start,stop)[dup])] <- stop[which(stop == c(start,stop)[dup])] - 1
}
    if (y == TRUE) {
        coord <- list(rep(start, each = 4), rep(stop, each = 4))
  } else if (y == FALSE) {
        coord <- list(rep(start, times = 4), rep(stop, times = 4))
  }
  return(coord)
}

x <- startstop(2000)
y <- startstop(1600, T)

sectorNos <- sectorCalc(x,y,DT)

startstop函数不是一个问题，但我需要一个更快的方法来子集数据表。必须对sectorCalc函数进行一些修改。 for循环是我能想到的最好的方法，但我没有太多的数据表经验。有关更快速地分解数据表的方法的任何想法？

The startstop function isn't really an issue but I need a faster way to subset the data table. Some modifications have to be made to the 'sectorCalc' function. The for loop was the best way I could think of but I don't have too much experience with data tables. Any ideas on a faster method of breaking up the data table?