Overview

The commonsMath package provides access to the Apache Commons Mathematics Library. It can can accessed via the:

We demonstrate below how to use it in:

Usage in R Scripts

Access via rscala

library("rscala")
s <- scala("commonsMath")
rng1 <- s$.new_org.apache.commons.math3.random.RandomDataGenerator()
rng1$reSeed(7342L)
rng1$nextGaussian(0,1)
## [1] -1.167763

Access via rJava

library("rJava")
.jinit(Sys.glob(file.path(system.file(package="commonsMath"), "java", "*.jar")))
rng2 <- .jnew("org.apache.commons.math3.random.RandomDataGenerator")
rng2$reSeed(.jlong(7342L))
rng2$nextGaussian(0,1)
## [1] -1.167763

Usage in R Packages

Access via rscala

The DESCRIPTION should have Imports: rscala, commonsMath.

The NAMESPACE should have import(rscala).

Define an .onLoad function like the following:

.onLoad <- function(libname, pkgname) {
  s <- scala("commonsMath")
  assign("s", s, envir = parent.env(environment()))
}

Package functions can then assess classes and methods from the commonsMath package, e.g.:

rstdnorm <- function() {
  rng1 <- s$.new_org.apache.commons.math3.random.RandomDataGenerator()
  rng1$nextGaussian(0.0,1.0)
}

Access via rJava

The DESCRIPTION should have Imports: rJava, commonsMath.

The NAMESPACE should first have import(rscala) and then have import(commonsMath).

Define an .onLoad function like the following:

.onLoad <- function(libname, pkgname) {
  .jpackage(pkgname, lib.loc=libname)
}

Package functions can then assess classes and methods from the commonsMath package, e.g.:

rstdnorm <- function() {
  rng2 <- .jnew("org.apache.commons.math3.random.RandomDataGenerator")
  rng2$nextGaussian(0,1)
}