Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

Found 10000 packages in 0.02 seconds

lzstring — by Sam Parmar, 10 months ago

Wrapper for 'lz-string' 'C++' Library

Provide access to the 'lz-string' < http://pieroxy.net/blog/pages/lz-string/index.html> 'C++' library for Lempel-Ziv (LZ) based compression and decompression of strings.

RcppTskit — by Gregor Gorjanc, 12 days ago

'R' Access to the 'tskit C' API

'Tskit' enables efficient storage, manipulation, and analysis of ancestral recombination graphs (ARGs) using succinct tree sequence encoding. The tree sequence encoding of an ARG is described in Wong et al. (2024) , while `tskit` project is described in Jeffrey et al. (2026) . See also < https://tskit.dev> for project news, documentation, and tutorials. 'Tskit' provides 'Python', 'C', and 'Rust' application programming interfaces (APIs). The 'Python' API can be called from 'R' via the 'reticulate' package to load and analyse tree sequences as described at < https://tskit.dev/tutorials/tskitr.html>. 'RcppTskit' provides 'R' access to the 'tskit C' API for cases where the 'reticulate' option is not optimal; for example, high-performance or low-level work with tree sequences. Currently, 'RcppTskit' provides a limited set of 'R' functions because the 'Python' API and 'reticulate' already covers most needs.

Rtsne — by Jesse Krijthe, 2 years ago

T-Distributed Stochastic Neighbor Embedding using a Barnes-Hut Implementation

An R wrapper around the fast T-distributed Stochastic Neighbor Embedding implementation by Van der Maaten (see < https://github.com/lvdmaaten/bhtsne/> for more information on the original implementation).

cppcontainers — by Christian Düben, 6 months ago

'C++' Standard Template Library Containers

Use 'C++' Standard Template Library containers interactively in R. Includes sets, unordered sets, multisets, unordered multisets, maps, unordered maps, multimaps, unordered multimaps, stacks, queues, priority queues, vectors, deques, forward lists, and lists.

ast2ast — by Krämer Konrad, 2 years ago

Translates an R Function to a C++ Function

Enable translation of a tiny subset of R to C++. The user has to define a R function which gets translated. For a full list of possible functions check the documentation. After translation an R function is returned which is a shallow wrapper around the C++ code. Alternatively an external pointer to the C++ function is returned to the user. The intention of the package is to generate fast functions which can be used as ode-system or during optimization.

stdvectors — by Marco Giuliano, 9 years ago

C++ Standard Library Vectors in R

Allows the creation and manipulation of C++ std::vector's in R.

RcppDE — by Dirk Eddelbuettel, 6 hours ago

Global Optimization by Differential Evolution in C++

An efficient C++ based implementation of the 'DEoptim' function which performs global optimization by differential evolution. Its creation was motivated by trying to see if the old approximation "easier, shorter, faster: pick any two" could in fact be extended to achieving all three goals while moving the code from plain old C to modern C++. The initial version did in fact do so, but a good part of the gain was due to an implicit code review which eliminated a few inefficiencies which have since been eliminated in 'DEoptim'.

abseil — by Xingchi Li, 2 years ago

'C++' Header Files from 'Abseil'

Wraps the 'Abseil' 'C++' library for use by R packages. Original files are from < https://github.com/abseil/abseil-cpp>. Patches are located at < https://github.com/doccstat/abseil-r/tree/main/local/patches>.

sanic — by Nikolas Kuschnig, 3 years ago

Solving Ax = b Nimbly in C++

Routines for solving large systems of linear equations and eigenproblems in R. Direct and iterative solvers from the Eigen C++ library are made available. Solvers include Cholesky, LU, QR, and Krylov subspace methods (Conjugate Gradient, BiCGSTAB). Dense and sparse problems are supported.

chicane — by Syed Haider, 4 years ago

Capture Hi-C Analysis Engine

Toolkit for processing and calling interactions in capture Hi-C data. Converts BAM files into counts of reads linking restriction fragments, and identifies pairs of fragments that interact more than expected by chance. Significant interactions are identified by comparing the observed read count to the expected background rate from a count regression model.