Last updated: 2025-02-28
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Knit directory: muse/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | f179c68 | Dave Tang | 2025-02-28 | File sizes with different distribution of zeros |
| html | 2574e2e | Dave Tang | 2025-02-28 | Build site. |
| Rmd | 8c6e5d6 | Dave Tang | 2025-02-28 | Exporting files out of R |
Create matrix with 99% zeros.
ngenes <- 16000
ncells <- 10000
matrix(
data = rbinom(n = ngenes*ncells, size = 1, prob = 0.01),
nrow = ngenes,
ncol = ncells
) -> my_mat
# theoretical number of zeros
ngenes*ncells*0.99[1] 158400000# number of zeros
sum(my_mat == 0)[1] 158400459Dense matrix object size.
object.size(my_mat)640000216 bytesExport dense matrix as rds.
dense_matrix <- "my_mat.rds"
saveRDS(object = my_mat, file = dense_matrix)Size of dense matrix file.
paste0(file.size(dense_matrix) / 1024 / 1024, " MBs")[1] "4.30414867401123 MBs"Convert to sparse matrix.
suppressPackageStartupMessages(library(Matrix))
my_mat_sparse <- as(my_mat, "sparseMatrix")
class(my_mat_sparse)[1] "dgCMatrix"
attr(,"package")
[1] "Matrix"Sparse matrix object size.
object.size(my_mat_sparse)19236000 bytesExport sparse matrix as rds.
sparse_matrix <- "my_mat_sparse.rds"
saveRDS(object = my_mat_sparse, file = sparse_matrix)Size of sparse matrix file.
paste0(file.size(sparse_matrix) / 1024 / 1024, " MBs")[1] "3.51174449920654 MBs"Clean up.
file.remove(dense_matrix)[1] TRUEfile.remove(sparse_matrix)[1] TRUEAs a workflow to check file sizes as we change the number of zeros.
file_size_wf <- function(prob, ngenes = 16000, ncells = 10000){
matrix(
data = rbinom(n = ngenes*ncells, size = 1, prob = prob),
nrow = ngenes,
ncol = ncells
) -> my_mat
my_mat_sparse <- as(my_mat, "sparseMatrix")
dense_matrix <- paste0("my_mat_", prob, ".rds")
saveRDS(object = my_mat, file = dense_matrix)
sparse_matrix <- paste0("my_mat_sparse_", prob, ".rds")
saveRDS(object = my_mat_sparse, file = sparse_matrix)
list(
prob = prob,
dense_size = paste0(file.size(dense_matrix) / 1024 / 1024, " MBs"),
sparse_size = paste0(file.size(sparse_matrix) / 1024 / 1024, " MBs")
) -> res
file.remove(dense_matrix)
file.remove(sparse_matrix)
return(res)
}
purrr::map_df(.x = c(0.01, 0.05, 0.25, 0.5), \(x) file_size_wf(x))# A tibble: 4 × 3
prob dense_size sparse_size
<dbl> <chr> <chr>
1 0.01 4.30162048339844 MBs 3.50793647766113 MBs
2 0.05 12.7624349594116 MBs 16.807599067688 MBs
3 0.25 32.0998592376709 MBs 79.5521965026855 MBs
4 0.5 38.3305673599243 MBs 144.26503276825 MBs
sessionInfo()R version 4.4.1 (2024-06-14)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 22.04.5 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0
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
time zone: Etc/UTC
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] Matrix_1.7-0 workflowr_1.7.1
loaded via a namespace (and not attached):
[1] jsonlite_1.8.9 dplyr_1.1.4 compiler_4.4.1 promises_1.3.0
[5] tidyselect_1.2.1 Rcpp_1.0.13 stringr_1.5.1 git2r_0.35.0
[9] callr_3.7.6 later_1.3.2 jquerylib_0.1.4 yaml_2.3.10
[13] fastmap_1.2.0 lattice_0.22-6 R6_2.5.1 generics_0.1.3
[17] knitr_1.48 tibble_3.2.1 rprojroot_2.0.4 bslib_0.8.0
[21] pillar_1.9.0 rlang_1.1.4 utf8_1.2.4 cachem_1.1.0
[25] stringi_1.8.4 httpuv_1.6.15 xfun_0.48 getPass_0.2-4
[29] fs_1.6.4 sass_0.4.9 cli_3.6.3 magrittr_2.0.3
[33] ps_1.8.1 grid_4.4.1 digest_0.6.37 processx_3.8.4
[37] rstudioapi_0.17.1 lifecycle_1.0.4 vctrs_0.6.5 evaluate_1.0.1
[41] glue_1.8.0 whisker_0.4.1 fansi_1.0.6 purrr_1.0.2
[45] rmarkdown_2.28 httr_1.4.7 tools_4.4.1 pkgconfig_2.0.3
[49] htmltools_0.5.8.1