OVERVIEW.md

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

Introduction

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.

Design goals

The objectives of the matrixStats package is to perform operations on matrices (i) as faster as possible, while (ii) not using unnecessary amounts of memory. These objectives drive the design, including the choice of the different defaults.

HenrikBengtsson/matrixStats documentation built on April 12, 2024, 5:32 a.m.