使用间隔分配分类值

Question

采用以下通用数据

A <- c(5,7,11,10,23,30,24,6)
B <- c(1,2,3,1,2,3,1,2)
C <- data.frame(A,B)

和以下间隔

library(intervals)
interval1 <- Intervals(
  matrix(
    c(
      5, 15,
      15, 25,
      25, 35,
      35, 100
    ),
    ncol = 2, byrow = TRUE
  ),
  closed = c( TRUE, FALSE ),
  type = "Z"
)
rownames(interval1) <- c("A","B","C", "D")

interval2 <- Intervals(
  matrix(
    c(
      0, 10,
      12, 20,
      22, 30,
      30, 100
    ),
    ncol = 2, byrow = TRUE
  ),
  closed = c( TRUE, FALSE ),
  type = "Z"
)
rownames(interval2) <- c("P","Q","R", "S")

现在我想创建以下输出表

因此,当A值与两个invalvals重叠时,我想将所有数据"复制"到下面的一行.我们还介绍了data$X哪个是interval1价值,data$y哪个是interval2价值.如果数据不适合任何间隔,我想从data.frame中删除它

我不确定该break()函数是否更适合用于创建间隔,或者该dplyr函数是否可用于生成重新固化数据行

Answer 1

您可以使用foverlaps在data.table:

library(data.table)
C.DT <- data.table(C)
C.DT[, A1:=A] # required for `foverlaps` so we can do a range search

# `D` and `E` are your interval matrices

I1 <- data.table(cbind(data.frame(D), idX=LETTERS[1:4], idY=NA))
I2 <- data.table(cbind(data.frame(E), idX=NA, idY=LETTERS[16:19]))

setkey(I1, X1, X2)  # set the keys on our interval ranges
setkey(I2, X1, X2)

rbind(
  foverlaps(C.DT, I1, by.x=c("A", "A1"), nomatch=0), # match every value in `C.DT$A` to the ranges in `I1` 
  foverlaps(C.DT, I2, by.x=c("A", "A1"), nomatch=0)
)[order(A, B), .(A, B, X=idX, Y=idY)]

生产:

     A B  X  Y
 1:  5 1  A NA
 2:  5 1 NA  P
 3:  6 2  A NA
 4:  6 2 NA  P
 5:  7 2  A NA
 6:  7 2 NA  P
 7: 10 1  A NA
 8: 10 1 NA  P
 9: 11 3  A NA
10: 23 2  B NA
11: 23 2 NA  R
12: 24 1  B NA
13: 24 1 NA  R
14: 30 3  C NA
15: 30 3 NA  R
16: 30 3 NA  S

请注意,您可以轻松地改变你得到的不是什么NA,通过修改其中的步骤I1和I2创建.