matrixStats: Functions that Apply to Rows and Columns of Matrices (and to Vectors)

The matrixStats package provides highly optimized functions for computing common summaries over rows and columns of matrices, e.g. rowQuantiles(). There are also functions that operate on vectors, e.g. logSumExp(). Their implementations strive to minimize both memory usage and processing time. They are often remarkably faster compared to good old apply() solutions. The calculations are mostly implemented in C, which allow us to optimize beyond what is possible to do in plain R. The package installs out-of-the-box on all common operating systems, including Linux, macOS and Windows.

Example

With a matrix

> x <- matrix(rnorm(20 * 500), nrow = 20, ncol = 500)

it is many times faster to calculate medians column by column using

> mu <- matrixStats::colMedians(x)

than using

> mu <- apply(x, MARGIN = 2, FUN = median)

Moreover, if performing calculations on a subset of rows and/or columns, using

> mu <- colMedians(x, rows = 33:158, cols = 1001:3000)

is much faster and more memory efficient than

> mu <- apply(x[33:158, 1001:3000], MARGIN = 2, FUN = median)

Benchmarks

For formal benchmarking of matrixStats functions relative to alternatives, see the Benchmark reports.

Installation

R package matrixStats is available on CRAN and can be installed in R as:

install.packages("matrixStats")

Pre-release version

To install the pre-release version that is available in Git branch develop on GitHub, use:

remotes::install_github("HenrikBengtsson/matrixStats@develop")

This will install the package from source. Because of this and because this package also compiles native code, Windows users need to have Rtools installed and macOS users need to have Xcode installed.

Contributions

This Git repository uses the Git Flow branching model (the git flow extension is useful for this). The develop branch contains the latest contributions and other code that will appear in the next release, and the master branch contains the code of the latest release, which is exactly what is currently on CRAN.

Contributing to this package is easy. Just send a pull request. When you send your PR, make sure develop is the destination branch on the matrixStats repository. Your PR should pass R CMD check --as-cran, which will also be checked by Travis CI and AppVeyor CI when the PR is submitted.

Software status

Resource:	CRAN	Travis CI	AppVeyor
Platforms:	Multiple	Linux & macOS	Windows
R CMD check
Test coverage