Package: parallelDist
Type: Package
Title: Parallel Distance Matrix Computation using Multiple Threads
Version: 0.1.0
Author: Alexander Eckert [aut, cre]
Authors@R: c(
    person("Alexander", "Eckert", role = c("aut", "cre"), email = "info@alexandereckert.com")
    )
Maintainer: Alexander Eckert <info@alexandereckert.com>
Description: A fast parallelized alternative to R's native 'dist' function to
    calculate distance matrices for continuous, binary, and multi-dimensional
    input matrices with support for a broad variety of distance functions from
    the 'stats', 'proxy' and 'dtw' R packages. 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 keeping the implementation flexible enough to support different step
    patterns and normalization methods.
License: GPL (>= 2)
LazyData: TRUE
URL: https://github.com/alexeckert/parallelDist,
        https://www.alexandereckert.com/R
BugReports: https://github.com/alexeckert/parallelDist/issues
NeedsCompilation: yes
Imports: Rcpp (>= 0.12.6), RcppParallel (>= 4.3.20)
LinkingTo: Rcpp, RcppParallel, RcppArmadillo
SystemRequirements: C++11
Suggests: dtw, ggplot2, proxy, highlight, testthat
VignetteBuilder: highlight
Packaged: 2017-06-06 07:26:30 UTC; user
Repository: CRAN
Date/Publication: 2017-06-06 10:18:20 UTC
