What is the difference between trunc () and as.integer ()?
What is the difference between trunc()
and as.integer()
?
Why as.integer
faster? Can someone please explain what's going on behind the curtain?
Why does it trunc()
return a class double
instead integer
?
x <- c(-3.2, -1.8, 2.3, 1.5, 1.500000001, -1.499999999)
trunc(x)
[1] -3 -1 2 1 1 -1
as.integer(x)
[1] -3 -1 2 1 1 -1
all.equal(trunc(x), as.integer(x))
[1] TRUE
sapply(list(trunc(x), as.integer(x)), typeof)
[1] "double" "integer"
library(microbenchmark)
x <- sample(seq(-5, 5, by = 0.001), size = 1e4, replace = TRUE)
microbenchmark(floor(x), trunc(x), as.integer(x), times = 1e4)
# I included floor() as well just to see the performance difference
Unit: microseconds
expr min lq mean median uq max neval
floor(x) 96.185 97.651 126.02124 98.237 99.411 67892.004 10000
trunc(x) 56.596 57.476 71.33856 57.770 58.649 2704.607 10000
as.integer(x) 16.422 16.715 23.26488 17.009 18.475 2828.064 10000
help(trunc)
:
"trunc takes one numeric argument, x, and returns a numeric vector containing integers formed by truncating the x values in the 0 direction.
help(as.integer)
:
"Non-integer numeric values are truncated to zero (ie as.integer (x) is equal to trunc (x)), [...]"
Background . I am writing functions to translate between different time and date representations, for example 120403 (hhmmss) -> 43443
(seconds from 00:00:00). Efficiency is all that matters.
Note: this question has nothing to do with floating point arithmetic
SessionInfo: R version 3.3.2, Windows 7 x64
source to share
From a technical point of view, these functions have different purposes.
The function trunc
removes the fractional part of numbers.
The function as.integer
converts input values to 32-bit integers.
Thus, as.integer
will overflow by large numbers (over 2 ^ 31):
x = 9876543210.5
sprintf("%15f", x)
# [1] "9876543210.500000"
sprintf("%15f", trunc(x))
# [1] "9876543210.000000"
as.integer(x)
# [1] NA
source to share