binCounts
matrixStats: Benchmark report
This report benchmark the performance of binCounts() against alternative methods.
- hist()
as below
> hist <- graphics::hist
> binCounts_hist <- function(x, bx, right = FALSE, ...) {
+ hist(x, breaks = bx, right = right, include.lowest = TRUE, plot = FALSE)$counts
+ }> set.seed(48879)
> nx <- 1e+05
> xmax <- 0.01 * nx
> x <- runif(nx, min = 0, max = xmax)
> storage.mode(x) <- mode
> str(x)
int [1:100000] 722 285 591 3 349 509 216 91 150 383 ...
> nb <- 10000
> bx <- seq(from = 0, to = xmax, length.out = nb + 1L)
> bx <- c(-1, bx, xmax + 1)> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 3054193 163.2 5709258 305.0 5709258 305.0
Vcells 5150348 39.3 22221311 169.6 56666022 432.4
> stats <- microbenchmark(binCounts = binCounts(x, bx = bx), hist = binCounts_hist(x, bx = bx), unit = "ms")Table: Benchmarking of binCounts() and hist() on integer+unsorted data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binCounts | 4.906438 | 4.981776 | 5.203014 | 5.038877 | 5.086733 | 9.428698 |
| 2 | hist | 8.540419 | 8.707266 | 8.860796 | 8.834853 | 8.920008 | 13.046789 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binCounts | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 2 | hist | 1.740656 | 1.747824 | 1.703012 | 1.753338 | 1.753583 | 1.383732 |
Figure: Benchmarking of binCounts() and hist() on integer+unsorted data. Outliers are displayed as crosses. Times are in milliseconds.
> x <- sort(x)> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 3053148 163.1 5709258 305.0 5709258 305.0
Vcells 5006313 38.2 22221311 169.6 56666022 432.4
> stats <- microbenchmark(binCounts = binCounts(x, bx = bx), hist = binCounts_hist(x, bx = bx), unit = "ms")Table: Benchmarking of binCounts() and hist() on integer+sorted data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binCounts | 0.746109 | 0.787845 | 0.8582377 | 0.8051165 | 0.8251675 | 4.630643 |
| 2 | hist | 3.649455 | 3.757657 | 6.1436541 | 3.8502230 | 3.9923265 | 217.726446 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binCounts | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.00000 |
| 2 | hist | 4.891316 | 4.769538 | 7.158453 | 4.782194 | 4.838201 | 47.01862 |
Figure: Benchmarking of binCounts() and hist() on integer+sorted data. Outliers are displayed as crosses. Times are in milliseconds.
> set.seed(48879)
> nx <- 1e+05
> xmax <- 0.01 * nx
> x <- runif(nx, min = 0, max = xmax)
> storage.mode(x) <- mode
> str(x)
num [1:100000] 722.11 285.54 591.33 3.42 349.14 ...
> nb <- 10000
> bx <- seq(from = 0, to = xmax, length.out = nb + 1L)
> bx <- c(-1, bx, xmax + 1)> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 3053211 163.1 5709258 305.0 5709258 305.0
Vcells 5056355 38.6 22221311 169.6 56666022 432.4
> stats <- microbenchmark(binCounts = binCounts(x, bx = bx), hist = binCounts_hist(x, bx = bx), unit = "ms")Table: Benchmarking of binCounts() and hist() on double+unsorted data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binCounts | 7.074370 | 7.339281 | 7.665371 | 7.397135 | 7.530170 | 12.55017 |
| 2 | hist | 8.758879 | 9.131600 | 9.299926 | 9.230472 | 9.331357 | 14.05749 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binCounts | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 2 | hist | 1.238114 | 1.244209 | 1.213239 | 1.247844 | 1.239196 | 1.120103 |
Figure: Benchmarking of binCounts() and hist() on double+unsorted data. Outliers are displayed as crosses. Times are in milliseconds.
> x <- sort(x)> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 3053277 163.1 5709258 305.0 5709258 305.0
Vcells 5056911 38.6 22267496 169.9 56666022 432.4
> stats <- microbenchmark(binCounts = binCounts(x, bx = bx), hist = binCounts_hist(x, bx = bx), unit = "ms")Table: Benchmarking of binCounts() and hist() on double+sorted data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binCounts | 0.627017 | 1.858442 | 2.001282 | 1.899146 | 1.933372 | 5.737497 |
| 2 | hist | 4.172153 | 4.382178 | 4.590442 | 4.465838 | 4.560886 | 8.298852 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binCounts | 1.000000 | 1.000000 | 1.00000 | 1.000000 | 1.000000 | 1.000000 |
| 2 | hist | 6.653971 | 2.357984 | 2.29375 | 2.351498 | 2.359031 | 1.446424 |
Figure: Benchmarking of binCounts() and hist() on double+sorted data. Outliers are displayed as crosses. Times are in milliseconds.
R version 3.6.1 Patched (2019-08-27 r77078)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.3 LTS
Matrix products: default
BLAS: /home/hb/software/R-devel/R-3-6-branch/lib/R/lib/libRblas.so
LAPACK: /home/hb/software/R-devel/R-3-6-branch/lib/R/lib/libRlapack.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] microbenchmark_1.4-6 matrixStats_0.55.0-9000 ggplot2_3.2.1
[4] knitr_1.24 R.devices_2.16.0 R.utils_2.9.0
[7] R.oo_1.22.0 R.methodsS3_1.7.1 history_0.0.0-9002
loaded via a namespace (and not attached):
[1] Biobase_2.45.0 bit64_0.9-7 splines_3.6.1
[4] network_1.15 assertthat_0.2.1 highr_0.8
[7] stats4_3.6.1 blob_1.2.0 robustbase_0.93-5
[10] pillar_1.4.2 RSQLite_2.1.2 backports_1.1.4
[13] lattice_0.20-38 glue_1.3.1 digest_0.6.20
[16] colorspace_1.4-1 sandwich_2.5-1 Matrix_1.2-17
[19] XML_3.98-1.20 lpSolve_5.6.13.3 pkgconfig_2.0.2
[22] genefilter_1.66.0 purrr_0.3.2 ergm_3.10.4
[25] xtable_1.8-4 mvtnorm_1.0-11 scales_1.0.0
[28] tibble_2.1.3 annotate_1.62.0 IRanges_2.18.2
[31] TH.data_1.0-10 withr_2.1.2 BiocGenerics_0.30.0
[34] lazyeval_0.2.2 mime_0.7 survival_2.44-1.1
[37] magrittr_1.5 crayon_1.3.4 statnet.common_4.3.0
[40] memoise_1.1.0 laeken_0.5.0 R.cache_0.13.0
[43] MASS_7.3-51.4 R.rsp_0.43.1 tools_3.6.1
[46] multcomp_1.4-10 S4Vectors_0.22.1 trust_0.1-7
[49] munsell_0.5.0 AnnotationDbi_1.46.1 compiler_3.6.1
[52] rlang_0.4.0 grid_3.6.1 RCurl_1.95-4.12
[55] cwhmisc_6.6 rappdirs_0.3.1 labeling_0.3
[58] bitops_1.0-6 base64enc_0.1-3 boot_1.3-23
[61] gtable_0.3.0 codetools_0.2-16 DBI_1.0.0
[64] markdown_1.1 R6_2.4.0 zoo_1.8-6
[67] dplyr_0.8.3 bit_1.1-14 zeallot_0.1.0
[70] parallel_3.6.1 Rcpp_1.0.2 vctrs_0.2.0
[73] DEoptimR_1.0-8 tidyselect_0.2.5 xfun_0.9
[76] coda_0.19-3 Total processing time was 7.73 secs.
To reproduce this report, do:
html <- matrixStats:::benchmark('binCounts')Copyright Henrik Bengtsson. Last updated on 2019-09-10 20:34:10 (-0700 UTC). Powered by RSP.
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