# Rcpp
# Extending Rcpp with Plugins
Within C++, one can set different compilation flags using:
// [[Rcpp::plugins(name)]]
List of the built-in plugins:
// built-in C++11 plugin
// [[Rcpp::plugins(cpp11)]]
// built-in C++11 plugin for older g++ compiler
// [[Rcpp::plugins(cpp0x)]]
// built-in C++14 plugin for C++14 standard
// [[Rcpp::plugins(cpp14)]]
// built-in C++1y plugin for C++14 and C++17 standard under development
// [[Rcpp::plugins(cpp1y)]]
// built-in OpenMP++11 plugin
// [[Rcpp::plugins(openmp)]]
# Inline Code Compile
Rcpp features two functions that enable code compilation inline and exportation directly into R: cppFunction()
and evalCpp()
. A third function called sourceCpp()
exists to read in C++ code in a separate file though can be used akin to cppFunction()
.
Below is an example of compiling a C++ function within R. Note the use of ""
to surround the source.
# Note - This is R code.
# cppFunction in Rcpp allows for rapid testing.
require(Rcpp)
# Creates a function that multiples each element in a vector
# Returns the modified vector.
cppFunction("
NumericVector exfun(NumericVector x, int i){
x = x*i;
return x;
}")
# Calling function in R
exfun(1:5, 3)
To quickly understand a C++ expression use:
# Use evalCpp to evaluate C++ expressions
evalCpp("std::numeric_limits<double>::max()")
## [1] 1.797693e+308
# Rcpp Attributes
Rcpp Attributes makes the process of working with R and C++ straightforward. The form of attributes take:
// [[Rcpp::attribute]]
The use of attributes is typically associated with:
// [[Rcpp::export]]
that is placed directly above a declared function header when reading in a C++ file via sourceCpp()
.
Below is an example of an external C++ file that uses attributes.
// Add code below into C++ file Rcpp_example.cpp
#include <Rcpp.h>
using namespace Rcpp;
// Place the export tag right above function declaration.
// [[Rcpp::export]]
double muRcpp(NumericVector x){
int n = x.size(); // Size of vector
double sum = 0; // Sum value
// For loop, note cpp index shift to 0
for(int i = 0; i < n; i++){
// Shorthand for sum = sum + x[i]
sum += x[i];
}
return sum/n; // Obtain and return the Mean
}
// Place dependent functions above call or
// declare the function definition with:
double muRcpp(NumericVector x);
// [[Rcpp::export]]
double varRcpp(NumericVector x, bool bias = true){
// Calculate the mean using C++ function
double mean = muRcpp(x);
double sum = 0;
int n = x.size();
for(int i = 0; i < n; i++){
sum += pow(x[i] - mean, 2.0); // Square
}
return sum/(n-bias); // Return variance
}
To use this external C++ file within R, we do the following:
require(Rcpp)
# Compile File
sourceCpp("path/to/file/Rcpp_example.cpp")
# Make some sample data
x = 1:5
all.equal(muRcpp(x), mean(x))
## TRUE
all.equal(varRcpp(x), var(x))
## TRUE
# Specifying Additional Build Dependencies
To use additional packages within the Rcpp ecosystem, the correct header file may not be Rcpp.h
but Rcpp<PACKAGE>.h
(as e.g. for RcppArmadillo (opens new window)). It typically needs to be imported and then the dependency is stated within
// [[Rcpp::depends(Rcpp<PACKAGE>)]]
Examples:
// Use the RcppArmadillo package
// Requires different header file from Rcpp.h
#include <RcppArmadillo.h>
// [[Rcpp::depends(RcppArmadillo)]]
// Use the RcppEigen package
// Requires different header file from Rcpp.h
#include <RcppEigen.h>
// [[Rcpp::depends(RcppEigen)]]