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SciViews - Miscellaneous Functions
Miscellaneous functions for SciViews or general use: manage a temporary environment attached to the search path for temporary variables you do not want to save() or load(), test if Aqua, Mac, Win, ... Show progress bar, etc.
Search Contributed R Packages, Sort by Package
Search contributed R packages, sort by package.
C++ Classes to Embed R in C++ Applications
C++ classes to embed R in C++ applications The 'RInside' packages makes it easier to have "R inside" your C++ application by providing a C++ wrapper class providing the R interpreter. As R itself is embedded into your application, a shared library build of R is required. This works on Linux, OS X and even on Windows provided you use the same tools used to build R itself. Numerous examples are provided in the eight subdirectories of the examples/ directory of the installed package: standard, mpi (for parallel computing) qt (showing how to embed 'RInside' inside a Qt GUI application), wt (showing how to build a "web-application" using the Wt toolkit), armadillo (for 'RInside' use with 'RcppArmadillo') and eigen (for 'RInside' use with 'RcppEigen'). The example use GNUmakefile(s) with GNU extensions, so a GNU make is required (and will use the GNUmakefile automatically). Doxygen-generated documentation of the C++ classes is available at the 'RInside' website as well.
'Rcpp' Integration for 'GNU GSL' Vectors and Matrices
'Rcpp' integration for 'GNU GSL' vectors and matrices The 'GNU Scientific Library' (or 'GSL') is a collection of numerical routines for scientific computing. It is particularly useful for C and C++ programs as it provides a standard C interface to a wide range of mathematical routines. There are over 1000 functions in total with an extensive test suite. The 'RcppGSL' package provides an easy-to-use interface between 'GSL' data structures and R using concepts from 'Rcpp' which is itself a package that eases the interfaces between R and C++. This package also serves as a prime example of how to build a package that uses 'Rcpp' to connect to another third-party library. The 'autoconf' script, 'inline' plugin and example package can all be used as a stanza to write a similar package against another library.
R Interface to the 'Protocol Buffers' 'API' (Version 2 or 3)
Protocol Buffers are a way of encoding structured data in an
efficient yet extensible format. Google uses Protocol Buffers for almost all
of its internal 'RPC' protocols and file formats. Additional documentation
is available in two included vignettes one of which corresponds to our 'JSS'
Examples using 'Rcpp' to Interface R and C++
Examples for Seamless R and C++ integration The 'Rcpp' package contains a C++ library that facilitates the integration of R and C++ in various ways. This package provides some usage examples. Note that the documentation in this package currently does not cover all the features in the package. It is not even close. On the other hand, the site < http://gallery.rcpp.org> is regrouping a large number of examples for 'Rcpp'.
Base64 Encoder and Decoder
Compatibility wrapper to replace the orphaned package by Romain Francois. New applications should use the 'openssl' or 'base64enc' package instead.
Deprecated 'classic' 'Rcpp' 'API'
The 'RcppClassic' package provides a deprecated C++ library which facilitates the integration of R and C++. New projects should use the new 'Rcpp' 'API' in the 'Rcpp' package.
'Rcpp' Integration for the 'Blaze' High-Performance C++ Math Library
'Blaze' is an open-source, high-performance C++ math library for dense and sparse arithmetic. With its state-of-the-art Smart Expression Template implementation 'Blaze' combines the elegance and ease of use of a domain-specific language with 'HPC'-grade performance, making it one of the most intuitive and fastest C++ math libraries available. The 'Blaze' library offers: - high performance through the integration of 'BLAS' libraries and manually tuned 'HPC' math kernels - vectorization by 'SSE', 'SSE2', 'SSE3', 'SSSE3', 'SSE4', 'AVX', 'AVX2', 'AVX-512', 'FMA', and 'SVML' - parallel execution by 'OpenMP', C++11 threads and 'Boost' threads ('Boost' threads are disabled in 'RcppBlaze') - the intuitive and easy to use API of a domain specific language - unified arithmetic with dense and sparse vectors and matrices - thoroughly tested matrix and vector arithmetic - completely portable, high quality C++ source code. The 'RcppBlaze' package includes the header files from the 'Blaze' library with disabling some functionalities related to link to the thread and system libraries which make 'RcppBlaze' be a header-only library. Therefore, users do not need to install 'Blaze' and the dependency 'Boost'. 'Blaze' is licensed under the New (Revised) BSD license, while 'RcppBlaze' (the 'Rcpp' bindings/bridge to 'Blaze') is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'. Note that since 'Blaze' has committed to 'C++14' commit to 'C++14' which does not used by most R users from version 3.0, we will use the version 2.6 of 'Blaze' which is 'C++98' compatible to support the most compilers and system.
Fast Linear Models for Objects from the 'bigmemory' Package
A reimplementation of the fastLm() functionality of 'RcppEigen' for big.matrix objects for fast out-of-memory linear model fitting.