从 data.table 库中取整/取整 ITime 格式时间的有效方法是什么

Question

What is the efficient way to round/floor ITime-formated time from data.table library?

The way I convert it is: I transform it to POSIXct, floor the result, and then convert it back to ITime. Example

library(lubridate)
library(data.table)

# Suppose I have some ITime variable:
Time = as.ITime( Sys.time() )

#That's what I do:
as.ITime( floor_date( as.POSIXct( Time ), "5 minutes"), format = "%H:%M:%S")

#Result:
[1] "16:05:00"

That works OK, but does not seem efficient because of the double converting. Is there a good alternative?

Answer 1

You could use the fact that an ITime variable is internally stored as an integer (number of seconds).

library(lubridate)
library(data.table)

# Let generate an ITime variable

set.seed(233)
y <- as.ITime(sample(60*60*24, size = 1e6, replace = TRUE))  # 60*60*24: max number of seconds in a day 

because 5 minutes are 60 * 5 seconds (300 seconds), you could divide your variable by 300, take its floor and then multiply back by 300. You can use the integer division operator, %/% , for the first two steps.

# head of the data using this method  and the one you suggested:
head(data.table(
    y = y,
    method1 = (y %/% 300L) * 300L,
    method2 = as.ITime( floor_date( as.POSIXct( y ), "5 minutes"), format = "%H:%M:%S")),
    n = 10)
  
           y  method1  method2
 1: 13:21:33 13:20:00 13:20:00
 2: 13:24:11 13:20:00 13:20:00
 3: 18:02:47 18:00:00 18:00:00
 4: 20:06:51 20:05:00 20:05:00
 5: 19:59:35 19:55:00 19:55:00
 6: 16:35:46 16:35:00 16:35:00
 7: 16:32:10 16:30:00 16:30:00
 8: 15:57:35 15:55:00 15:55:00
 9: 01:21:16 01:20:00 01:20:00
10: 17:10:09 17:10:00 17:10:00

Timing

microbenchmark::microbenchmark(
  method1 = (y %/% 300L) * 300L,
  method2 = as.ITime( floor_date( as.POSIXct( y ), "5 minutes"), format = "%H:%M:%S"),
  times = 5L
)

Unit: milliseconds
    expr      min       lq      mean   median       uq      max neval
 method1   7.5192   7.7691   8.23544   8.0286   8.8695   8.9908     5
 method2 396.5867 404.5420 418.07694 412.6798 436.3783 440.1979     5