【发布时间】：2020-06-03 19:17:40
【问题描述】：
问题：我怎样才能使下面代码中的 for 循环更高效地运行？对于这个玩具示例，它可以在合理的时间内工作。但是，unique_ids 将是一个包含大约 8000 个条目的向量，并且 for 循环会大大降低计算速度。有任何想法吗？非常感谢！
目的： 根据 for 循环中的计算逻辑，将每天的 IID 追溯聚类到 hop 和 top。
初始数据：
IID ENTRY FINISH TARGET max_finish_target_date
1: 1 2020-02-11 2020-02-19 2020-02-15 2020-02-19
2: 2 2020-02-13 2020-02-17 2020-02-19 2020-02-19
最终（目标）数据：
IID Dates ind_frist
1: 1 2020-02-10
2: 1 2020-02-11 hop
3: 1 2020-02-12 hop
4: 1 2020-02-13 hop
5: 1 2020-02-14 hop
6: 1 2020-02-15 hop
7: 1 2020-02-16 top
8: 1 2020-02-17 top
9: 1 2020-02-18 top
10: 1 2020-02-19 top
11: 2 2020-02-10
12: 2 2020-02-11
13: 2 2020-02-12
14: 2 2020-02-13 hop
15: 2 2020-02-14 hop
16: 2 2020-02-15 hop
17: 2 2020-02-16 hop
18: 2 2020-02-17 hop
19: 2 2020-02-18
20: 2 2020-02-19
21: 3 2020-02-10
22: 3 2020-02-11
23: 3 2020-02-12
24: 3 2020-02-13
25: 3 2020-02-14
26: 3 2020-02-15 hop
27: 3 2020-02-16 hop
28: 3 2020-02-17 top
29: 3 2020-02-18 top
30: 3 2020-02-19 top
代码
rm(list = ls())
library(data.table)
# Some sample start data
initial_dt <- data.table(IID = c(1, 2, 3),
ENTRY = c("2020-02-11", "2020-02-13", "2020-02-15"),
FINISH = c("2020-02-19", "2020-02-17", ""),
TARGET = c("2020-02-15", "2020-02-19", "2020-02-16"))
initial_dt[, ":="(ENTRY = ymd(ENTRY),
FINISH = ymd(FINISH),
TARGET = ymd(TARGET))]
initial_dt[is.na(FINISH), FINISH := as.Date(ymd_hms(Sys.time()), format = "%Y-%m-%d")]
initial_dt[, max_finish_target_date := pmax(FINISH, TARGET)]
# Specify target data shape and output format
unique_ids <- c(1, 2, 3)
dts <- seq(as.Date("2020-02-10", format = "%Y-%m-%d"), as.Date(ymd_hms(Sys.time()), format = "%Y-%m-%d"), by = "days")
ids <- rep(unique_ids, each = length(dts))
len <- length(unique_ids)
final_dt <- data.table(IID = ids,
Dates = rep(dts, times = len))
# Calculation logic
# QUESTION: How can I make this part below run more efficiently and less time costly?
for (d_id in unique_ids){
final_dt[(IID == d_id) & (Dates %between% c(initial_dt[IID == d_id, ENTRY], initial_dt[IID == d_id, max_finish_target_date])),
ind_frist := ifelse((Dates > initial_dt[IID == d_id, TARGET]) & (Dates <= initial_dt[IID == d_id, max_finish_target_date]),
"hop",
"top")]
}
【问题讨论】：
-
您需要为
data.table设置您的唯一密钥。您还需要使用内置的for i j操作，该操作非常占用内存并且不会复制数据。看看套族for (i in from:to) set(DT, row, column, new value)来源：brooksandrew.github.io/simpleblog/articles/advanced-data-table/… -
您的问题中显示的目标数据与您的 for 循环的输出不同。
标签： r performance for-loop data.table