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DESCRIPTION

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Package: Rcpp
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Title: Seamless R and C++ Integration
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Version: 0.11.2.4
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Date: 2014-09-10
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Version: 0.11.2.6
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Date: 2014-09-21
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Author: Dirk Eddelbuettel, Romain Francois, JJ Allaire, Kevin Ushey,
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Douglas Bates, and John Chambers
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Maintainer: Dirk Eddelbuettel <[email protected]>
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Description: The Rcpp package provides R functions as well as a C++ classes
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which facilitate the integration of R and C++.
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.
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R data types (SEXP) are matched to C++ objects in a class hierarchy. All R
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types are supported (vectors, functions, environment, etc ...) and each
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type is mapped to a dedicated class. For example, numeric vectors are
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represented as instances of the Rcpp::NumericVector class, environments are
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represented as instances of Rcpp::Environment, functions are represented as
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Rcpp::Function, etc ... The "Rcpp-introduction" vignette provides a good
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entry point to Rcpp.
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.
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Conversion from C++ to R and back is driven by the templates Rcpp::wrap
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and Rcpp::as which are highly flexible and extensible, as documented
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in the "Rcpp-extending" vignette.
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.
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Rcpp also provides Rcpp modules, a framework that allows exposing
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C++ functions and classes to the R level. The "Rcpp-modules" vignette
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details the current set of features of Rcpp-modules.
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.
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Rcpp includes a concept called Rcpp sugar that brings many R functions
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into C++. Sugar takes advantage of lazy evaluation and expression templates
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to achieve great performance while exposing a syntax that is much nicer
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to use than the equivalent low-level loop code. The "Rcpp-sugar" vignette
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gives an overview of the feature.
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.
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Rcpp attributes provide a high-level syntax for declaring C++
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functions as callable from R and automatically generating the code
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required to invoke them. Attributes are intended to facilitate both
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interactive use of C++ within R sessions as well as to support R
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package development. Attributes are built on top of Rcpp modules and
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their implementation is based on previous work in the inline package.
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.
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Many examples are included, and around 900 unit tests in 446 unit
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test functions provide additional usage examples.
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.
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An earlier version of Rcpp, containing what we now call the 'classic Rcpp
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API' was written during 2005 and 2006 by Dominick Samperi. This code has
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been factored out of Rcpp into the package RcppClassic, and it is still
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available for code relying on the older interface. New development should
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always use this Rcpp package instead.
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.
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Additional documentation is available via the paper by Eddelbuettel and
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Francois (2011, JSS) paper and the book by Eddelbuettel (2013, Springer);
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see 'citation("Rcpp")' for details.
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which offer a seamless integration of R and C++. Many R data types and objects
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can be mapped back and forth to C++ equivalents which facilitates both writing
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of new code as well as easier integration of third-party libraries. Extensive
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documentation about Rcpp is provided by several vignettes included in this
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package, via the Rcpp Gallery site at http://gallery.rcpp.org, the paper by
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Eddelbuettel and Francois (2011, JSS), and the book by Eddelbuettel (2013,
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Springer); see 'citation("Rcpp")' for details on these last two.
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Depends: R (>= 3.0.0)
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Imports: methods
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Suggests: RUnit, inline, rbenchmark, highlight, pkgKitten (>= 0.1.2)

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