R,如何将此操作矢量化

在R中,我怎样才能最好地矢量化这个操作？

我有一个参考值表,具有较低的(A)和较高的(B)限制.

我还有一个值表(X)来查找上表.

对于X的每个值,我需要确定它是否位于参考表中A和B的任何值之间.

为了演示上述内容,以下是使用循环的解决方案:

#For Reproduceability,
set.seed(1); 

#Set up the Reference and Lookup Tables
nref = 5; nlook = 10
referenceTable <- data.frame(A=runif(nref,min=0.25,max=0.5),
                             B=runif(nref,min=0.50,max=0.75));
lookupTable    <- data.frame(X=runif(nlook),IsIn=0)

#Process for each row in the lookup table
#search for at least one match in the reference table where A <= X < B
for(x in 1:nrow(lookupTable)){
  v   <- lookupTable$X[x]
  tmp <- subset(referenceTable,v >= A & v < B)
  lookupTable[x,'IsIn'] = as.integer(nrow(tmp) > 0)
}

我正在尝试删除该for(x in .... )组件,因为我现实生活中的表中存在数千条记录.

我找不到确切的欺骗,所以这是一个可能的解决方案data.table::foverlaps.首先,我们需要添加一个额外的列lookupTable,以便在两侧创建边界.然后key在referenceTable(必要的foverlaps工作),然后只需运行一个简单的重叠加入而只选择先加入,因为你想要的任何连接(我用0^,以转换为二进制,因为你不想要的实际位置)

library(data.table)
setDT(lookupTable)[, Y := X] # Add an additional boundary column
setkey(setDT(referenceTable)) # Key the referenceTable data set
lookupTable[, IsIn := 0 ^ !foverlaps(lookupTable, 
                                     referenceTable, 
                                     by.x = c("X", "Y"),
                                     mult = "first", 
                                     nomatch = 0L, 
                                     which = TRUE)]
#             X IsIn         Y
#  1: 0.2059746    0 0.2059746
#  2: 0.1765568    0 0.1765568
#  3: 0.6870228    1 0.6870228
#  4: 0.3841037    1 0.3841037
#  5: 0.7698414    0 0.7698414
#  6: 0.4976992    1 0.4976992
#  7: 0.7176185    1 0.7176185
#  8: 0.9919061    0 0.9919061
#  9: 0.3800352    1 0.3800352
# 10: 0.7774452    0 0.7774452