Package: arrApply 2.2

Serguei Sokol

arrApply: Apply a Function to a Margin of an Array

High performance variant of apply() for a fixed set of functions. Considerable speedup of this implementation is a trade-off for universality: user defined functions cannot be used with this package. However, about 20 most currently employed functions are available for usage. They can be divided in three types: reducing functions (like mean(), sum() etc., giving a scalar when applied to a vector), mapping function (like normalise(), cumsum() etc., giving a vector of the same length as the input vector) and finally, vector reducing function (like diff() which produces result vector of a length different from the length of input vector). Optional or mandatory additional arguments required by some functions (e.g. norm type for norm()) can be passed as named arguments in '...'.

Authors:Serguei Sokol

arrApply_2.2.tar.gz
arrApply_2.2.tar.gz(r-4.5-noble)arrApply_2.2.tar.gz(r-4.4-noble)
arrApply_2.2.tgz(r-4.4-emscripten)arrApply_2.2.tgz(r-4.3-emscripten)
arrApply.pdf |arrApply.html
arrApply/json (API)
NEWS

# Install 'arrApply' in R:
install.packages('arrApply', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

1.48 score 1 packages 7 scripts 330 downloads 1 exports 2 dependencies

Last updated 2 years agofrom:1165feb7c9. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 08 2024
R-4.5-linux-x86_64NOTEDec 08 2024

Exports:arrApply

Dependencies:RcppRcppArmadillo