matrixStats.benchmarks
binCounts() benchmarks on subsetted computation
This report benchmark the performance of binCounts() on subsetted computation.
Data type “integer”
Non-sorted simulated data
> 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)
> idxs <- sample.int(length(x), size = length(x) * 0.7)
Results
> x_S <- x[idxs]
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5154501 275.3 8529671 455.6 8529671 455.6
Vcells 20249600 154.5 49807323 380.0 60562128 462.1
> stats <- microbenchmark(binCounts_x_S = binCounts(x_S, bx = bx), `binCounts(x, idxs)` = binCounts(x,
+ idxs = idxs, bx = bx), `binCounts(x[idxs])` = binCounts(x[idxs], bx = bx), unit = "ms")
Table: Benchmarking of binCounts_x_S(), binCounts(x, idxs)() and binCounts(x[idxs])() 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_x_S | 3.743131 | 3.848801 | 4.127887 | 3.922297 | 4.027184 | 8.920197 |
| 2 | binCounts(x, idxs) | 3.893024 | 4.004293 | 4.168872 | 4.096316 | 4.166940 | 5.471601 |
| 3 | binCounts(x[idxs]) | 3.857521 | 4.031572 | 4.236317 | 4.106948 | 4.205989 | 8.409583 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binCounts_x_S | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.0000000 |
| 2 | binCounts(x, idxs) | 1.040045 | 1.040400 | 1.009929 | 1.044367 | 1.034703 | 0.6133946 |
| 3 | binCounts(x[idxs]) | 1.030560 | 1.047488 | 1.026268 | 1.047077 | 1.044399 | 0.9427575 |
Figure: Benchmarking of binCounts_x_S(), binCounts(x, idxs)() and binCounts(x[idxs])() on integer+unsorted data. Outliers are displayed as crosses. Times are in milliseconds.
Sorted simulated data
> x <- sort(x)
> idxs <- sort(idxs)
> x_S <- x[idxs]
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5144884 274.8 8529671 455.6 8529671 455.6
Vcells 9089908 69.4 39845859 304.0 60562128 462.1
> stats <- microbenchmark(binCounts_x_S = binCounts(x_S, bx = bx), `binCounts(x, idxs)` = binCounts(x,
+ idxs = idxs, bx = bx), `binCounts(x[idxs])` = binCounts(x[idxs], bx = bx), unit = "ms")
Table: Benchmarking of binCounts_x_S(), binCounts(x, idxs)() and binCounts(x[idxs])() 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_x_S | 0.385435 | 0.4092300 | 0.4817315 | 0.4294950 | 0.4709225 | 3.929690 |
| 3 | binCounts(x[idxs]) | 0.518729 | 0.5491750 | 0.6191970 | 0.5692775 | 0.6047635 | 4.079936 |
| 2 | binCounts(x, idxs) | 0.516765 | 0.5495165 | 0.6299195 | 0.5742815 | 0.6159210 | 4.122084 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binCounts_x_S | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 3 | binCounts(x[idxs]) | 1.345827 | 1.341972 | 1.285357 | 1.325458 | 1.284210 | 1.038234 |
| 2 | binCounts(x, idxs) | 1.340732 | 1.342806 | 1.307615 | 1.337109 | 1.307903 | 1.048959 |
Figure: Benchmarking of binCounts_x_S(), binCounts(x, idxs)() and binCounts(x[idxs])() on integer+sorted data. Outliers are displayed as crosses. Times are in milliseconds.
Data type “double”
Non-sorted simulated data
> 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)
> idxs <- sample.int(length(x), size = length(x) * 0.7)
Results
> x_S <- x[idxs]
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5144954 274.8 8529671 455.6 8529671 455.6
Vcells 9175467 70.1 31876688 243.2 60562128 462.1
> stats <- microbenchmark(binCounts_x_S = binCounts(x_S, bx = bx), `binCounts(x, idxs)` = binCounts(x,
+ idxs = idxs, bx = bx), `binCounts(x[idxs])` = binCounts(x[idxs], bx = bx), unit = "ms")
Table: Benchmarking of binCounts_x_S(), binCounts(x, idxs)() and binCounts(x[idxs])() 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_x_S | 5.105216 | 5.257010 | 5.446426 | 5.342236 | 5.421011 | 9.558161 |
| 3 | binCounts(x[idxs]) | 5.338782 | 5.499212 | 5.578754 | 5.533915 | 5.628005 | 6.476944 |
| 2 | binCounts(x, idxs) | 5.312807 | 5.492083 | 5.723801 | 5.556865 | 5.667785 | 9.995764 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binCounts_x_S | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 3 | binCounts(x[idxs]) | 1.045751 | 1.046072 | 1.024296 | 1.035880 | 1.038184 | 0.677635 |
| 2 | binCounts(x, idxs) | 1.040663 | 1.044716 | 1.050928 | 1.040176 | 1.045522 | 1.045783 |
Figure: Benchmarking of binCounts_x_S(), binCounts(x, idxs)() and binCounts(x[idxs])() on double+unsorted data. Outliers are displayed as crosses. Times are in milliseconds.
Sorted simulated data
> x <- sort(x)
> idxs <- sort(idxs)
> x_S <- x[idxs]
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 5145028 274.8 8529671 455.6 8529671 455.6
Vcells 9175516 70.1 31876688 243.2 60562128 462.1
> stats <- microbenchmark(binCounts_x_S = binCounts(x_S, bx = bx), `binCounts(x, idxs)` = binCounts(x,
+ idxs = idxs, bx = bx), `binCounts(x[idxs])` = binCounts(x[idxs], bx = bx), unit = "ms")
Table: Benchmarking of binCounts_x_S(), binCounts(x, idxs)() and binCounts(x[idxs])() 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_x_S | 1.093777 | 1.187210 | 1.283248 | 1.216720 | 1.255538 | 4.833301 |
| 3 | binCounts(x[idxs]) | 1.256096 | 1.349684 | 1.423724 | 1.376073 | 1.399282 | 4.866945 |
| 2 | binCounts(x, idxs) | 1.266017 | 1.345908 | 1.434421 | 1.387024 | 1.414468 | 4.888036 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binCounts_x_S | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 3 | binCounts(x[idxs]) | 1.148402 | 1.136854 | 1.109469 | 1.130969 | 1.114488 | 1.006961 |
| 2 | binCounts(x, idxs) | 1.157473 | 1.133673 | 1.117804 | 1.139970 | 1.126583 | 1.011325 |
Figure: Benchmarking of binCounts_x_S(), binCounts(x, idxs)() and binCounts(x[idxs])() on double+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_0.60.1 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] rappdirs_0.3.3 startup_0.15.0 labeling_0.4.2
[67] bitops_1.0-7 base64enc_0.1-3 boot_1.3-28
[70] gtable_0.3.0 DBI_1.1.1 markdown_1.1
[73] R6_2.5.1 lpSolveAPI_5.5.2.0-17.7 rle_0.9.2
[76] dplyr_1.0.7 fastmap_1.1.0 bit_4.0.4
[79] utf8_1.2.2 parallel_4.1.1 Rcpp_1.0.7
[82] vctrs_0.3.8 png_0.1-7 DEoptimR_1.0-9
[85] tidyselect_1.1.1 xfun_0.25 coda_0.19-4
Total processing time was 6.89 secs.
Reproducibility
To reproduce this report, do:
html <- matrixStats:::benchmark('binCounts_subset')
Copyright Dongcan Jiang. Last updated on 2021-08-25 18:48:51 (+0200 UTC). Powered by RSP.