3D Visualization Using OpenGL

Provides medium to high level functions for 3D interactive graphics, including functions modelled on base graphics (plot3d(), etc.) as well as functions for constructing representations of geometric objects (cube3d(), etc.). Output may be on screen using OpenGL, or to various standard 3D file formats including WebGL, PLY, OBJ, STL as well as 2D image formats, including PNG, Postscript, SVG, PGF.

Manage Massive Matrices with Shared Memory and Memory-Mapped Files

Create, store, access, and manipulate massive matrices. Matrices are allocated to shared memory and may use memory-mapped files. Packages 'biganalytics', 'bigtabulate', 'synchronicity', and 'bigalgebra' provide advanced functionality.

Lightweight and Feature Complete Unit Testing Framework

Provides a lightweight (zero-dependency) and easy to use unit testing framework. Main features: install tests with the package. Test results are treated as data that can be stored and manipulated. Test files are R scripts interspersed with test commands, that can be programmed over. Fully automated build-install-test sequence for packages. Skip tests when not run locally (e.g. on CRAN). Flexible and configurable output printing. Compare computed output with output stored with the package. Run tests in parallel. Extensible by other packages. Report side effects.

A S3 Class for Vectors of 64bit Integers

Package 'bit64' provides serializable S3 atomic 64bit (signed) integers. These are useful for handling database keys and exact counting in +-2^63. WARNING: do not use them as replacement for 32bit integers, integer64 are not supported for subscripting by R-core and they have different semantics when combined with double, e.g. integer64 + double => integer64. Class integer64 can be used in vectors, matrices, arrays and data.frames. Methods are available for coercion from and to logicals, integers, doubles, characters and factors as well as many elementwise and summary functions. Many fast algorithmic operations such as 'match' and 'order' support inter- active data exploration and manipulation and optionally leverage caching.

'Rcpp' Integration for the 'Armadillo' Templated Linear Algebra Library

'Armadillo' is a templated C++ linear algebra library aiming towards a good balance between speed and ease of use. It provides high-level syntax and functionality deliberately similar to Matlab. It is useful for algorithm development directly in C++, or quick conversion of research code into production environments. It provides efficient classes for vectors, matrices and cubes where dense and sparse matrices are supported. Integer, floating point and complex numbers are supported. A sophisticated expression evaluator (based on template meta-programming) automatically combines several operations to increase speed and efficiency. Dynamic evaluation automatically chooses optimal code paths based on detected matrix structures. Matrix decompositions are provided through integration with LAPACK, or one of its high performance drop-in replacements (such as 'MKL' or 'OpenBLAS'). It can automatically use 'OpenMP' multi-threading (parallelisation) to speed up computationally expensive operations. The 'RcppArmadillo' package includes the header files from the 'Armadillo' library; users do not need to install 'Armadillo' itself in order to use 'RcppArmadillo'. Starting from release 15.0.0, the minimum compilation standard is C++14 so 'Armadillo' version 14.6.3 is included as a fallback when an R package forces the C++11 standard. Package authors should set a '#define' to select the 'current' version, or select the 'legacy' version (also chosen as default) if they must. See 'GitHub issue #475' for details. Since release 7.800.0, 'Armadillo' is licensed under Apache License 2; previous releases were under licensed as MPL 2.0 from version 3.800.0 onwards and LGPL-3 prior to that; 'RcppArmadillo' (the 'Rcpp' bindings/bridge to Armadillo) is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'.

'Rcpp' Integration for the 'Eigen' Templated Linear Algebra Library

R and 'Eigen' integration using 'Rcpp'. 'Eigen' is a C++ template library for linear algebra: matrices, vectors, numerical solvers and related algorithms. It supports dense and sparse matrices on integer, floating point and complex numbers, decompositions of such matrices, and solutions of linear systems. Its performance on many algorithms is comparable with some of the best implementations based on 'Lapack' and level-3 'BLAS'. The 'RcppEigen' package includes the header files from the 'Eigen' C++ template library. Thus users do not need to install 'Eigen' itself in order to use 'RcppEigen'. Since version 3.1.1, 'Eigen' is licensed under the Mozilla Public License (version 2); earlier version were licensed under the GNU LGPL version 3 or later. 'RcppEigen' (the 'Rcpp' bindings/bridge to 'Eigen') is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'.

Read, Write, Format Excel 2007 and Excel 97/2000/XP/2003 Files

Provide R functions to read/write/format Excel 2007 and Excel 97/2000/XP/2003 file formats.

Read, Write and Edit 'xlsx' Files

Simplifies the creation of 'xlsx' files by providing a high level interface to writing, styling and editing worksheets.

Read and Write ODS Files

Read ODS (OpenDocument Spreadsheet) into R as data frame. Also support writing data frame into ODS file.

A Simple HTTP Server to Serve Static Files or Dynamic Documents

Start an HTTP server in R to serve static files, or dynamic documents that can be converted to HTML files (e.g., R Markdown) under a given directory.