Package: parallelDist 0.2.6

Alexander Eckert

parallelDist: Parallel Distance Matrix Computation using Multiple Threads

A fast parallelized alternative to R's native 'dist' function to calculate distance matrices for continuous, binary, and multi-dimensional input matrices, which supports a broad variety of 41 predefined distance functions from the 'stats', 'proxy' and 'dtw' R packages, as well as user- defined functions written in C++. For ease of use, the 'parDist' function extends the signature of the 'dist' function and uses the same parameter naming conventions as distance methods of existing R packages. The package is mainly implemented in C++ and leverages the 'RcppParallel' package to parallelize the distance computations with the help of the 'TinyThread' library. Furthermore, the 'Armadillo' linear algebra library is used for optimized matrix operations during distance calculations. The curiously recurring template pattern (CRTP) technique is applied to avoid virtual functions, which improves the Dynamic Time Warping calculations while the implementation stays flexible enough to support different DTW step patterns and normalization methods.

Authors:Alexander Eckert [aut, cre], Lucas Godoy [ctb], Srikanth KS [ctb]

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NEWS

# Install parallelDist in R:
install.packages('parallelDist', repos = c('https://fastverse.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/alexeckert/paralleldist/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

data-sciencedistance-computationsmatrices

2 exports 49 stars 3.96 score 3 dependencies 13 dependents 1.9k downloads

Last updated 2 years agofrom:ef7086596f301bc2ea619e2998f0a79c69a87b52

Exports:parallelDistparDist

Dependencies:RcppRcppArmadilloRcppParallel

parallelDist vignette

Rendered fromparallelDist.Rnwusingutils::Sweaveon Jun 09 2024.

Last update: 2022-02-02
Started: 2017-06-06