which_first, introduced in version 0.5.0, caused by an overeliance on compiler optimization. (#20)pminV no longer accept non-numeric inputdo_ functions have been removed entirelypmax0(x, in_place = TRUE) now returns early, rather than checking the vector twice.sum_isna now reflects sum(is.na(x)) when x contains NaN.sum_isna diverts ALTREP vectors to anyNA for performance and to avoid problems when passed to C++.which_last for the first index from the last index.divisible and divisible16 for returning divisibilitycount_logical fast tabulation of logical vectorsand3s, or3s, parallelized and separated versions of &sum_and3s and sum_or3s, the sums of the above logical vectors.whichs for an alterantive implementation of which which separates the inputwhich_firstNA and which_lastNA for first/last position of missing valueswhich_first accepts argument use.which.max for better performance on known short inputsis_constant now accepts nThread for multithreaded checking of constant vectors and is much faster in general even in single-thread mode.sum_isna now accepts nThread for multithreaded accumulation of missing value countsare_even can be slightly faster on integers if ignoring NA, handles large doubles (like 1e10), and accepts nThread.is_safe2int(x) now tolerates NaN input. Thanks to CRAN clang-UBSAN.which_first(x == y) now works properly when length(y) == length(x).xor2 a faster version of xor.set.seed(1)
library(hutils)
library(hutilscpp)
bench__mark <- function(...) {
dplyr::select(bench::mark(..., min_iterations = 12),
expression, median, `itr/sec`, mem_alloc, n_gc)
}
x <- y <- logical(1e9)
bench__mark(xor(x, y), xor2(x, y))
#> Warning: Some expressions had a GC in every iteration; so filtering is
#> disabled.
#> # A tibble: 2 x 5
#> expression median `itr/sec` mem_alloc n_gc
#> <chr> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 xor(x, y) 7.956s 0.126 14.901GB 16
#> 2 xor2(x, y) 1.652s 0.530 3.725GB 3
x <- !y
bench__mark(xor(x, y), xor2(x, y))
#> Warning: Some expressions had a GC in every iteration; so filtering is
#> disabled.
#> # A tibble: 2 x 5
#> expression median `itr/sec` mem_alloc n_gc
#> <chr> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 xor(x, y) 8.227s 0.121 14.901GB 13
#> 2 xor2(x, y) 1.983s 0.460 3.725GB 3
x <- samp(c(TRUE, FALSE), 1e9)
y <- samp(c(TRUE, FALSE), 1e9)
bench__mark(xor(x, y), xor2(x, y))
#> # A tibble: 2 x 5
#> expression median `itr/sec` mem_alloc n_gc
#> <chr> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 xor(x, y) 20.276s 0.0493 14.901GB 11
#> 2 xor2(x, y) 1.971s 0.506 3.725GB 3
x <- samp(c(TRUE, FALSE, NA), 1e9)
y <- samp(c(TRUE, FALSE), 1e9)
benc__mark(xor(x, y), xor2(x, y))
#> # A tibble: 2 x 5
#> expression median `itr/sec` mem_alloc n_gc
#> <chr> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 xor(x, y) 25.063s 0.0399 14.901GB 2
#> 2 xor2(x, y) 4.524s 0.221 3.725GB 3Created on 2019-08-25 by the reprex package (v0.3.0)
NEWS.md file to track changes to the package.which_first(x == y) now supports logical x without returning arcane error messages.is_constant, for testing atomic vectors and isntConstant for the first different valueis_sorted and isntSorted (currently private), similarly.and3, or3 for ternary and/or enabling vectorized short-circuitingsum_isna for counting NA values.pminC now handles integer inputs without coercing to double.pmaxC(x, a) accepts integer a when x is type double.pmax0 and pmin0 perform much better, especially when x is known and marked as sorted, but also due to a better algorithm using absolute value.set.seed(1)
attach(asNamespace("hutilscpp"))
#> The following object is masked from package:base:
#>
#> isFALSE
bench__mark <- function(...) {
dplyr::select(bench::mark(..., min_iterations = 12),
expression, median, `itr/sec`, mem_alloc, n_gc)
}
x <- rep_len(rlnorm(1e6, 7, 2), 1e9)
bench__mark(do_pmaxC_dbl(x, 0), do_pmax0_abs_dbl(x))
#> # A tibble: 2 x 5
#> expression median `itr/sec` mem_alloc n_gc
#> <chr> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 do_pmaxC_dbl(x, 0) 2428.139ms 0.405 3618205.211KB 4
#> 2 do_pmax0_abs_dbl(x) 777.362ms 1.28 6.539KB 0
x <- x - 1
bench__mark(do_pmaxC_dbl(x, 0), do_pmax0_abs_dbl(x))
#> # A tibble: 2 x 5
#> expression median `itr/sec` mem_alloc n_gc
#> <chr> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 do_pmaxC_dbl(x, 0) 2.394s 0.410 3.451GB 4
#> 2 do_pmax0_abs_dbl(x) 2.590s 0.386 3.451GB 4
x <- sort(x)
bench__mark(do_pmaxC_dbl(x, 0), do_pmax0_radix_sorted_dbl(x))
#> # A tibble: 2 x 5
#> expression median `itr/sec` mem_alloc n_gc
#> <chr> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 do_pmaxC_dbl(x, 0) 3.593s 0.313 6.901GB 5
#> 2 do_pmax0_radix_sorted_dbl(x) 2.306s 0.437 3.451GB 4
x <- rep_len(as.integer(rlnorm(1e6, 7, 2)), 1e9)
bench__mark(do_pmaxC_int(x, 0L), do_pmax0_abs_int(x))
#> # A tibble: 2 x 5
#> expression median `itr/sec` mem_alloc n_gc
#> <chr> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 do_pmaxC_int(x, 0L) 2041.515ms 0.490 3906256.727KB 3
#> 2 do_pmax0_abs_int(x) 405.266ms 2.45 6.539KB 0
x <- x - 1L
bench__mark(do_pmaxC_int(x, 0L), do_pmax0_abs_int(x))
#> # A tibble: 2 x 5
#> expression median `itr/sec` mem_alloc n_gc
#> <chr> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 do_pmaxC_int(x, 0L) 1.449s 0.686 3.725GB 2
#> 2 do_pmax0_abs_int(x) 1.766s 0.577 3.725GB 1
x <- sort(x)
bench__mark(do_pmaxC_int(x, 0L), do_pmax0_radix_sorted_int(x))
#> # A tibble: 2 x 5
#> expression median `itr/sec` mem_alloc n_gc
#> <chr> <bch:tm> <dbl> <bch:byt> <dbl>
#> 1 do_pmaxC_int(x, 0L) 1.751s 0.568 7.451GB 2
#> 2 do_pmax0_radix_sorted_int(x) 1.404s 0.827 3.725GB 1Created on 2019-08-10 by the reprex package (v0.3.0)