A fast parallelized alternative to R's native 'dist' function to calculate distance matrices for continuous, binary, and multidimensional input matrices, which supports a broad variety of 39 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.
Package details 


Author  Alexander Eckert [aut, cre] 
Date of publication  20171204 23:47:31 UTC 
Maintainer  Alexander Eckert <[email protected]> 
License  GPL (>= 2) 
Version  0.2.1 
URL  https://github.com/alexeckert/parallelDist https://www.alexandereckert.com/R 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.