从i和j中的data.table按组进行随机抽样

Question

我花了一些时间试图弄清楚当data.table组中的行here，here或here从i中随机抽样时发生了什么在library(data.table) library(magrittr) seed <- 2016 set.seed(seed) size <- 10 dt <- data.table( id = 1:size, A = sample(letters[1:3], size, replace = TRUE), B = 'N', C = sample(1:100, size, replace = TRUE) + sample(30:70, size, replace = TRUE)) 组内。

从一些设置开始：

set.seed(seed)
dt[, .N, by = A]
dt[, .N, by = A][, N] %>% sapply(function(x) { sample(x, round(x*0.5)) })
#    A N
# 1: a 6
# 2: c 2
# 3: b 2
#
# Which gives the following rows:
# a: 2, 1, 4
# c: 1
# b: 1
# 
# So the result should be:
#     id A B   C | order in sampled dt
#  1:  1 a N  82 | 2
#  2:  2 a N  86 | 1
#  3:  3 c N  68 | 4
#  4:  4 a N 140 | 
#  5:  5 b N  92 | 5
#  6:  6 a N  94 | 3
#  7:  7 b N 102 | 
#  8:  8 c N  69 | 
#  9:  9 a N 126 | 
# 10: 10 a N  56 | 

检查应采样的行：

# Results as below or just columns A and I (or V1) with ids:
#    id A B  C
# 1:  2 a N 86
# 2:  1 a N 82
# 3:  6 a N 94
# 4:  3 c N 68
# 5:  5 b N 92

# Get .I and sample from them:
set.seed(seed)
dt[, .I, by = A] %>%
  .[, .SD[sample(.N, round(.N*0.5))], by = A]
set.seed(seed)
dt[, .I[sample(.N, round(.N*0.5))], by = A]
# Both returning expected ids

# Sample from .SD
set.seed(seed)
dt[, .SD[sample(.N, round(.N*0.5))], by = A]
# Correct, but populating each .SD, i.e. can be slow

# Sample from .I and use in i (to e.g. change some values in j)
set.seed(seed)
dt[dt[, .I[sample(.N, round(.N*0.5))], by = A]$V1, ]
set.seed(seed)
dt[dt[, sample(.I, round(.N*0.5)), by = A]$V1, ]
# Correct and faster than above

确认：A的顺序是其值在dt中的顺序？

一些“正确”的样本：

set.seed(seed)
dt[sample(.N, round(.N*0.5)), .I, by = A]
#    A  I
# 1: a  2
# 2: a 10
# 3: a  1
# 4: b  7
# 5: c  3

set.seed(seed)
dt[sample(.N, round(.N*0.5)), .SD, by = A]
#    id A B   C
# 1:  2 a N  86
# 2: 10 a N  56
# 3:  1 a N  82
# 4:  7 b N 102
# 5:  3 c N  68

问题：那些抽样是什么？

i

这显然与{{1}}内的抽样有关，但我无法弄清究到究竟发生了什么。