matrixStats.benchmarks
binMeans() benchmarks
This report benchmark the performance of binMeans() against alternative methods.
Alternative methods
- binMeans_R()
which is defined as
> binMeans_R <- function(y, x, bx, na.rm = FALSE, count = TRUE, right = FALSE) {
+ B <- length(bx) - 1L
+ res <- double(B)
+ counts <- integer(B)
+ for (kk in seq_len(B)) {
+ if (right) {
+ idxs <- which(bx[kk] < x & x <= bx[kk + 1L])
+ } else {
+ idxs <- which(bx[kk] <= x & x < bx[kk + 1L])
+ }
+ yKK <- y[idxs]
+ muKK <- mean(yKK)
+ res[kk] <- muKK
+ counts[kk] <- length(idxs)
+ }
+ if (count)
+ attr(res, "count") <- counts
+ res
+ }
Results
Non-sorted simulated data
> nx <- 10000
> set.seed(48879)
> x <- runif(nx, min = 0, max = 1)
> y <- runif(nx, min = 0, max = 1)
> nb <- 1000
> bx <- seq(from = 0, to = 1, length.out = nb + 1L)
> bx <- c(-1, bx, 2)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5170903 276.2 7916910 422.9 7916910 422.9
Vcells 9346669 71.4 33191153 253.3 53339345 407.0
> stats <- microbenchmark(binMeans = binMeans(x = x, y = y, bx = bx, count = TRUE), binMeans_R = binMeans_R(x = x,
+ y = y, bx = bx, count = TRUE), unit = "ms")
Table: Benchmarking of binMeans() and binMeans_R() on unsorted data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binMeans | 0.682249 | 0.7374175 | 0.8813661 | 0.7774885 | 0.811816 | 6.048626 |
| 2 | binMeans_R | 73.402751 | 78.9574815 | 83.5650250 | 80.1633250 | 81.700767 | 418.862456 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binMeans | 1.0000 | 1.000 | 1.00000 | 1.0000 | 1.0000 | 1.00000 |
| 2 | binMeans_R | 107.5894 | 107.073 | 94.81307 | 103.1055 | 100.6395 | 69.24919 |
Figure: Benchmarking of binMeans() and binMeans_R() on unsorted data. Outliers are displayed as crosses. Times are in milliseconds.
Sorted simulated data
> x <- sort(x)
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5156709 275.4 7916910 422.9 7916910 422.9
Vcells 9068253 69.2 33191153 253.3 53339345 407.0
> stats <- microbenchmark(binMeans = binMeans(x = x, y = y, bx = bx, count = TRUE), binMeans_R = binMeans_R(x = x,
+ y = y, bx = bx, count = TRUE), unit = "ms")
Table: Benchmarking of binMeans() and binMeans_R() on sorted data. The top panel shows times in milliseconds and the bottom panel shows relative times.
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binMeans | 0.266934 | 0.2912505 | 0.3275638 | 0.322542 | 0.35919 | 0.515872 |
| 2 | binMeans_R | 57.947255 | 63.0138950 | 63.3220839 | 63.718875 | 64.45944 | 68.680471 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binMeans | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 | 1.0000 |
| 2 | binMeans_R | 217.0846 | 216.3563 | 193.3122 | 197.5522 | 179.4578 | 133.1347 |
Figure: Benchmarking of binMeans() and binMeans_R() on sorted data. Outliers are displayed as crosses. Times are in milliseconds.
Appendix
Session information
R version 4.1.1 Patched (2021-08-10 r80727)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.5 LTS
Matrix products: default
BLAS: /home/hb/software/R-devel/R-4-1-branch/lib/R/lib/libRblas.so
LAPACK: /home/hb/software/R-devel/R-4-1-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_1.4-7 matrixStats_0.60.0 ggplot2_3.3.5
[4] knitr_1.33 R.devices_2.17.0 R.utils_2.10.1
[7] R.oo_1.24.0 R.methodsS3_1.8.1-9001 history_0.0.1-9000
loaded via a namespace (and not attached):
[1] Biobase_2.52.0 httr_1.4.2 splines_4.1.1
[4] bit64_4.0.5 network_1.17.1 assertthat_0.2.1
[7] highr_0.9 stats4_4.1.1 blob_1.2.2
[10] GenomeInfoDbData_1.2.6 robustbase_0.93-8 pillar_1.6.2
[13] RSQLite_2.2.8 lattice_0.20-44 glue_1.4.2
[16] digest_0.6.27 XVector_0.32.0 colorspace_2.0-2
[19] Matrix_1.3-4 XML_3.99-0.7 pkgconfig_2.0.3
[22] zlibbioc_1.38.0 genefilter_1.74.0 purrr_0.3.4
[25] ergm_4.1.2 xtable_1.8-4 scales_1.1.1
[28] tibble_3.1.4 annotate_1.70.0 KEGGREST_1.32.0
[31] farver_2.1.0 generics_0.1.0 IRanges_2.26.0
[34] ellipsis_0.3.2 cachem_1.0.6 withr_2.4.2
[37] BiocGenerics_0.38.0 mime_0.11 survival_3.2-13
[40] magrittr_2.0.1 crayon_1.4.1 statnet.common_4.5.0
[43] memoise_2.0.0 laeken_0.5.1 fansi_0.5.0
[46] R.cache_0.15.0 MASS_7.3-54 R.rsp_0.44.0
[49] progressr_0.8.0 tools_4.1.1 lifecycle_1.0.0
[52] S4Vectors_0.30.0 trust_0.1-8 munsell_0.5.0
[55] tabby_0.0.1-9001 AnnotationDbi_1.54.1 Biostrings_2.60.2
[58] compiler_4.1.1 GenomeInfoDb_1.28.1 rlang_0.4.11
[61] grid_4.1.1 RCurl_1.98-1.4 cwhmisc_6.6
[64] rstudioapi_0.13 rappdirs_0.3.3 startup_0.15.0
[67] labeling_0.4.2 bitops_1.0-7 base64enc_0.1-3
[70] boot_1.3-28 gtable_0.3.0 DBI_1.1.1
[73] markdown_1.1 R6_2.5.1 lpSolveAPI_5.5.2.0-17.7
[76] rle_0.9.2 dplyr_1.0.7 fastmap_1.1.0
[79] bit_4.0.4 utf8_1.2.2 parallel_4.1.1
[82] Rcpp_1.0.7 vctrs_0.3.8 png_0.1-7
[85] DEoptimR_1.0-9 tidyselect_1.1.1 xfun_0.25
[88] coda_0.19-4
Total processing time was 16.51 secs.
Reproducibility
To reproduce this report, do:
html <- matrixStats:::benchmark('binMeans')
Copyright Henrik Bengtsson. Last updated on 2021-08-25 22:09:46 (+0200 UTC). Powered by RSP.