CRAN
arrApply 2.1
Apply a Function to a Margin of an Array
Released Mar 8, 2019 by Serguei Sokol
Dependencies
RcppArmadillo 0.9.200.7.1 Rcpp
High performance variant of apply() for a fixed set of functions. Considerable speedup is a trade-off for universality, user defined functions cannot be used with this package. However, 21 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() or normalise() functions) can be passed as named arguments in '...'.
Installation
Maven
This package can be included as a dependency from a Java or Scala project by including
the following your project's pom.xml
file.
Read more
about embedding Renjin in JVM-based projects.
<dependencies> <dependency> <groupId>org.renjin.cran</groupId> <artifactId>arrApply</artifactId> <version>2.1-b1</version> </dependency> </dependencies> <repositories> <repository> <id>bedatadriven</id> <name>bedatadriven public repo</name> <url>https://nexus.bedatadriven.com/content/groups/public/</url> </repository> </repositories>
Renjin CLI
If you're using Renjin from the command line, you load this library by invoking:
library('org.renjin.cran:arrApply')
Test Results
This package was last tested against Renjin 0.9.2724 on Mar 10, 2019.