dsLib (data-science library) is designed to facilite common and necessary tasks which are currently missing or not automated in other packages. This package tries to provide functions to improve and facilite the reproducibility and efficiency of data analysis by examining and returning the following information from script or set of code instructions:
- Computing time
- Memory usage
- Versions of code (from Git) and R session information
For example, if we need to track the memory usage and computing time from a chunk of code, dsLib provides a simple way to do it as shown below:
inicio("Sleep for 5 seconds")
Sys.sleep(5)
fin()Which returns the following information
==>(18/Oct/2019 01:24:24): Sleep for 5 seconds ...
>> Current mem use = 46.8 MB
>> Final mem use = 46.8 MB
>>> Elapsed time: 5.054 secs
==> DONE!
inicio()records the date and time, and prints out an optional message indicating the purpose of the code section. Finally, the memory usage in the current R session is displayed belowfin()calculates the overal difference in memory usage since the execution ofinicio(). This function also records and prints out the elased time sinceinicio()was run and prints out a DONE! message indicating that the execution of the code section has been finished
By using the pair inicio() / fin() it is possible to locally monitor the memory usage and execution time from a script. Furthermore, it may be used as a proxy to track the code location resulting on an error after the execution of a script.
print_session() provides the git status of the last commit (if git is being used for version control) along with the current R session information.
Example:
print_session()The first output section corresponds to the information of the last commit:
- Git details:
Commit: b183f61f6deb060ad4e1b9b823305e13ae82d599
Message: fixes CHECK errors from documentation
name: joseah
email: [email protected]
when: 2019-10-17 13:44:55
The next section is the R session details obtained via devtools::session_info()
─ Session info ──────────────────────────────────────────────────────────────
setting value
version R version 3.6.0 (2019-04-26)
os macOS Mojave 10.14.6
system x86_64, darwin15.6.0
ui RStudio
language (EN)
collate en_AU.UTF-8
ctype en_AU.UTF-8
tz Australia/Sydney
date 2019-10-18
─ Packages ──────────────────────────────────────────────────────────────────
package * version date lib source
assertthat 0.2.1 2019-03-21 [1] CRAN (R 3.6.0)
backports 1.1.4 2019-04-10 [1] CRAN (R 3.6.0)
callr 3.3.1 2019-07-18 [1] CRAN (R 3.6.0)
cli 1.1.0 2019-03-19 [1] CRAN (R 3.6.0)
codetools 0.2-16 2018-12-24 [1] CRAN (R 3.6.0)
crayon 1.3.4 2017-09-16 [1] CRAN (R 3.6.0)
desc 1.2.0 2018-05-01 [1] CRAN (R 3.6.0)
devtools 2.1.0 2019-07-06 [1] CRAN (R 3.6.0)
digest 0.6.20 2019-07-04 [1] CRAN (R 3.6.0)
dsLib 0.1.0 2019-10-17 [1] local
fs 1.3.1 2019-05-06 [1] CRAN (R 3.6.0)
git2r 0.26.1 2019-06-29 [1] CRAN (R 3.6.0)
glue 1.3.1 2019-03-12 [1] CRAN (R 3.6.0)
here 0.1 2017-05-28 [1] CRAN (R 3.6.0)
magrittr 1.5 2014-11-22 [1] CRAN (R 3.6.0)
memoise 1.1.0 2017-04-21 [1] CRAN (R 3.6.0)
pkgbuild 1.0.3 2019-03-20 [1] CRAN (R 3.6.0)
pkgload 1.0.2 2018-10-29 [1] CRAN (R 3.6.0)
prettyunits 1.0.2 2015-07-13 [1] CRAN (R 3.6.0)
processx 3.4.1 2019-07-18 [1] CRAN (R 3.6.0)
pryr 0.1.4 2018-02-18 [1] CRAN (R 3.6.0)
ps 1.3.0 2018-12-21 [1] CRAN (R 3.6.0)
R6 2.4.0 2019-02-14 [1] CRAN (R 3.6.0)
Rcpp 1.0.2 2019-07-25 [1] CRAN (R 3.6.0)
remotes 2.1.0 2019-06-24 [1] CRAN (R 3.6.0)
rlang 0.4.0 2019-06-25 [1] CRAN (R 3.6.0)
rprojroot 1.3-2 2018-01-03 [1] CRAN (R 3.6.0)
rstudioapi 0.10 2019-03-19 [1] CRAN (R 3.6.0)
sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 3.6.0)
stringi 1.4.3 2019-03-12 [1] CRAN (R 3.6.0)
stringr 1.4.0 2019-02-10 [1] CRAN (R 3.6.0)
testthat 2.2.1 2019-07-25 [1] CRAN (R 3.6.0)
tictoc 1.0 2014-06-17 [1] CRAN (R 3.6.0)
usethis 1.5.1 2019-07-04 [1] CRAN (R 3.6.0)
withr 2.1.2 2018-03-15 [1] CRAN (R 3.6.0)
[1] /Library/Frameworks/R.framework/Versions/3.6/Resources/library
The output from print_session() is shown in the R terminal and printed to a file called session.info. The output path of this file is the current working directory.
The rotate_x() function allows to rotate the x-axis lables by default by 90 degrees. This function is shorter and more intuitive than rotating the labels via element_text(angle = angle, hjust = 1) within the theme function.
The function no_legend() removes the legend automatically if added after the theme set-up.
An example on rotate_x() and no_legend() is shown below:
library("ggplot2")
library("dsLib")
ggplot(iris, aes(Species, Sepal.Length, fill = Species)) +
geom_boxplot() +
theme_classic() +
scale_fill_brewer(palette = "Set1") +
rotate_x() +
no_legend()To facilitate the concatenation of strings, dsLib provides the %p% operator.
Example:
"ACG" %p% "TCG" %p% "CCC"Output:
[1] "ACGTCGCCC"
%p% is a wrapper for paste0() but allows the flexibility of using the function as an operator.
Sometimes, it is ideal to explore the first dimensions of an object to have an idea about its content. Although head(), str() and glimpse() are some options, they provide more information than needed and/or are greatly verbose.
The function glance() subsets the first n elements in m dimensions from a vector, matrix, Matrix::Matrix, list, or data.frame.
Example:
glance(Seurat::pbmc_small@raw.data)Output:
5 x 5 sparse Matrix of class "dgTMatrix"
ATGCCAGAACGACT CATGGCCTGTGCAT GAACCTGATGAACC TGACTGGATTCTCA AGTCAGACTGCACA
MS4A1 . . . . .
CD79B 1 . . . .
CD79A . . . . .
HLA-DRA . 1 . . 1
TCL1A . . . . .
glance() returns the first 5 rows and columns from a sparse Matrix object. Unlike head(), glance() operates in all dimensions of the object.