binCounts_subset - HenrikBengtsson/matrixStats GitHub Wiki
matrixStats: Benchmark report
This report benchmark the performance of binCounts() on subsetted computation.
> 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)> x_S <- x[idxs]
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 3053531 163.1 5709258 305 5709258 305.0
Vcells 16188101 123.6 34595238 264 56666022 432.4
> 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 | 3.464805 | 3.516767 | 3.848541 | 3.584201 | 4.049233 | 8.374912 |
| 3 | binCounts(x[idxs]) | 3.631464 | 3.711681 | 3.989712 | 3.735329 | 3.951278 | 11.965669 |
| 2 | binCounts(x, idxs) | 3.620185 | 3.716548 | 3.921681 | 3.751879 | 4.284023 | 4.448815 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binCounts_x_S | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.0000000 |
| 3 | binCounts(x[idxs]) | 1.048101 | 1.055424 | 1.036682 | 1.042165 | 0.975809 | 1.4287516 |
| 2 | binCounts(x, idxs) | 1.044845 | 1.056808 | 1.019005 | 1.046783 | 1.057984 | 0.5312074 |
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.
> x <- sort(x)
> idxs <- sort(idxs)> x_S <- x[idxs]
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 3050781 163.0 5709258 305.0 5709258 305.0
Vcells 5051589 38.6 27676191 211.2 56666022 432.4
> 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 | 0.342860 | 0.3640255 | 0.4647694 | 0.3752860 | 0.3901185 | 3.723007 |
| 2 | binCounts(x, idxs) | 0.545045 | 0.5866205 | 0.7336247 | 0.6044015 | 0.6292265 | 4.455126 |
| 3 | binCounts(x[idxs]) | 0.544250 | 0.5880440 | 0.7073336 | 0.6047335 | 0.6287325 | 3.960708 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binCounts_x_S | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.000000 |
| 2 | binCounts(x, idxs) | 1.589701 | 1.611482 | 1.578470 | 1.610509 | 1.612911 | 1.196647 |
| 3 | binCounts(x[idxs]) | 1.587383 | 1.615392 | 1.521902 | 1.611394 | 1.611645 | 1.063846 |
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.
> 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)> x_S <- x[idxs]
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 3050851 163.0 5709258 305 5709258 305.0
Vcells 5137148 39.2 22140953 169 56666022 432.4
> 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 | 4.749294 | 4.886123 | 5.151806 | 4.961504 | 5.471378 | 9.023233 |
| 3 | binCounts(x[idxs]) | 5.022232 | 5.180465 | 5.564606 | 5.241095 | 5.465776 | 12.838464 |
| 2 | binCounts(x, idxs) | 4.996679 | 5.178938 | 5.505466 | 5.260656 | 5.770683 | 9.607470 |
| expr | min | lq | mean | median | uq | max | |
|---|---|---|---|---|---|---|---|
| 1 | binCounts_x_S | 1.000000 | 1.000000 | 1.000000 | 1.000000 | 1.0000000 | 1.000000 |
| 3 | binCounts(x[idxs]) | 1.057469 | 1.060240 | 1.080127 | 1.056352 | 0.9989763 | 1.422823 |
| 2 | binCounts(x, idxs) | 1.052089 | 1.059928 | 1.068648 | 1.060294 | 1.0547039 | 1.064748 |
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.
> x <- sort(x)
> idxs <- sort(idxs)> x_S <- x[idxs]
> gc()
used (Mb) gc trigger (Mb) max used (Mb)
Ncells 3050925 163.0 5709258 305.0 5709258 305.0
Vcells 5137197 39.2 22186262 169.3 56666022 432.4
> 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 | 1.093218 | 1.172178 | 1.336594 | 1.198812 | 1.225707 | 4.533939 |
| 3 | binCounts(x[idxs]) | 1.320847 | 1.432406 | 1.536461 | 1.452905 | 1.475132 | 5.270048 |
| 2 | binCounts(x, idxs) | 1.330347 | 1.435493 | 1.538992 | 1.454046 | 1.475350 | 4.798756 |
| 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]) | 1.208219 | 1.222004 | 1.149534 | 1.211954 | 1.203496 | 1.162355 |
| 2 | binCounts(x, idxs) | 1.216909 | 1.224637 | 1.151428 | 1.212906 | 1.203673 | 1.058408 |
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.
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 6.8 secs.
To reproduce this report, do:
html <- matrixStats:::benchmark('binCounts_subset')Copyright Dongcan Jiang. Last updated on 2019-09-10 20:34:01 (-0700 UTC). Powered by RSP.
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