Rcpp v0.12.11

0

Monthly downloads

0th

Percentile

Seamless R and C++ Integration

The 'Rcpp' package provides R functions as well as C++ classes which offer a seamless integration of R and C++. Many R data types and objects can be mapped back and forth to C++ equivalents which facilitates both writing of new code as well as easier integration of third-party libraries. Documentation about 'Rcpp' is provided by several vignettes included in this package, via the 'Rcpp Gallery' site at <http://gallery.rcpp.org>, the paper by Eddelbuettel and Francois (2011, JSS), and the book by Eddelbuettel (2013, Springer); see 'citation("Rcpp")' for details on these last two.

Readme

Rcpp Build Status License CRAN Downloads Coverage Status

Seamless R and C++ Integration

The Rcpp package provides R functions and a C++ library facilitating the integration of R and C++.

R data types (SEXP) are matched to C++ objects in a class hierarchy. All R types are supported (vectors, functions, environment, etc ...) and each type is mapped to a dedicated class. For example, numeric vectors are represented as instances of the Rcpp::NumericVector class, environments are represented as instances of Rcpp::Environment, functions are represented as Rcpp::Function, etc ... The Rcpp-introduction vignette (also published as a JSS paper) provides a good entry point to Rcpp as do the Rcpp website, the Rcpp page and the Rcpp Gallery. Full documentation is provided by the Rcpp book.

Conversion from C++ to R and back is driven by the templates Rcpp::wrap and Rcpp::as which are highly flexible and extensible, as documented in the Rcpp-extending vignette.

Rcpp also provides Rcpp modules, a framework that allows exposing C++ functions and classes to the R level. The Rcpp-modules vignette details the current set of features of Rcpp-modules.

Rcpp includes a concept called Rcpp sugar that brings many R functions into C++. Sugar takes advantage of lazy evaluation and expression templates to achieve great performance while exposing a syntax that is much nicer to use than the equivalent low-level loop code. The Rcpp-sugar gives an overview of the feature.

Rcpp attributes provide a high-level syntax for declaring C++ functions as callable from R and automatically generating the code required to invoke them. Attributes are intended to facilitate both interactive use of C++ within R sessions as well as to support R package development. Attributes are built on top of Rcpp modules and their implementation is based on previous work in the inline package. See the Rcpp-atttributes vignettes for more details.

Documentation

The package ships with nine pdf vignettes.

Additional documentation is available via the JSS paper by Eddelbuettel and Francois (2011, JSS) paper (corresponding to the 'intro' vignette) and the book by Eddelbuettel (2013, Springer); see 'citation("Rcpp")' for details.

Examples

The Rcpp Gallery showcases over one hundred fully documented and working examples.

A number of examples are included as are 1385 unit tests in 599 unit test functions provide additional usage examples.

An earlier version of Rcpp, containing what we now call the 'classic Rcpp API' was written during 2005 and 2006 by Dominick Samperi. This code has been factored out of Rcpp into the package RcppClassic, and it is still available for code relying on the older interface. New development should always use this Rcpp package instead.

Other usage examples are provided by packages using Rcpp. As of March 2017, there are 975 CRAN packages using Rcpp, a further 89 BioConductor packages in its current release as well as an unknown number of GitHub, Bitbucket, R-Forge, ... repositories using Rcpp. All these packages provide usage examples for Rcpp.

Installation

Released and tested versions of Rcpp are available via the CRAN network, and can be installed from within R via

install.packages("Rcpp")

To install from source, ensure you have a complete package development environment for R as discussed in the relevant documentation; also see questions 1.2 and 1.3 in the Rcpp-FAQ.

Authors

Dirk Eddelbuettel, Romain Francois, JJ Allaire, Kevin Ushey, Qiang Kou, Nathan Russell, Doug Bates, and John Chambers

License

GPL (>= 2)

Functions in Rcpp

Name Description
C++Object-class c++ internal objects
C++OverloadedMethods-class Class "C++OverloadedMethods"
Module
Rcpp-deprecated Deprecated Functions in the Rcpp Package
.DollarNames-methods completion
Module-class Rcpp modules
C++Class-class Reflection information for an internal c++ class
C++Constructor-class Class "C++Constructor"
C++Field-class Class "C++Field"
C++Function-class Class "C++Function"
compileAttributes
compilerCheck Check for Minimal (g++) Compiler Version
exportAttribute Rcpp::export Attribute
exposeClass
LdFlags (Deprecated) Rcpp Linker Flags
RcppUnitTests Rcpp : unit tests results
dependsAttribute Rcpp::depends Attribute
evalCpp
Rcpp.package.skeleton
Rcpp.plugin.maker
pluginsAttribute Rcpp::plugins Attribute
populate
sourceCpp
cppFunction
demangle
Rcpp-internal Rcpp internal functions
Rcpp-package R / C++ interface
formals<--methods Set the formal arguments of a C++ function
interfacesAttribute Rcpp::interfaces Attribute
registerPlugin
setRcppClass
loadModule
loadRcppModules-deprecated
No Results!

Last month downloads

Details

Date 2017-05-20
VignetteBuilder highlight
URL http://www.rcpp.org, http://dirk.eddelbuettel.com/code/rcpp.html, https://github.com/RcppCore/Rcpp
License GPL (>= 2)
BugReports https://github.com/RcppCore/Rcpp/issues
MailingList Please send questions and comments regarding Rcpp to rcpp-devel@lists.r-forge.r-project.org
RoxygenNote 5.0.1
NeedsCompilation yes
Packaged 2017-05-20 12:07:21.962471 UTC; edd
Repository CRAN
Date/Publication 2017-05-22 04:18:02 UTC

Include our badge in your README

[![Rdoc](http://www.rdocumentation.org/badges/version/Rcpp)](http://www.rdocumentation.org/packages/Rcpp)