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wannesm/dtaidistance v2.0.0

Wannes Meert; Kilian Hendrickx; Toon Van Craenendonck


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  <dc:creator>Wannes Meert</dc:creator>
  <dc:creator>Kilian Hendrickx</dc:creator>
  <dc:creator>Toon Van Craenendonck</dc:creator>
  <dc:date>2020-08-12</dc:date>
  <dc:description>New in v2:


	Numpy is now an optional dependency, also to compile the C library (only Cython is required).
	Small optimizations throughout the C code to improve speed.
	The consistent use of size_t instead of int allows for larger data structures on 64 bit machines and be more compatible with Numpy.
	The parallelization is now implemented directly in C (included if OpenMP is installed).
	The max_dist argument turned out to be similar to Silva and Batista's work on PrunedDTW [7]. The toolbox now implements a version that is equal to PrunedDTW since it prunes more partial distances. Additionally, a use_pruning argument is added to automatically set max_dist to the Euclidean distance, as suggested by Silva and Batista, to speed up the computation (a new method ub_euclidean is available).
	Support in the C library for multi-dimensional sequences in the dtaidistance.dtw_ndim package.
</dc:description>
  <dc:identifier>https://zenodo.org/record/3981067</dc:identifier>
  <dc:identifier>10.5281/zenodo.3981067</dc:identifier>
  <dc:identifier>oai:zenodo.org:3981067</dc:identifier>
  <dc:relation>url:https://github.com/wannesm/dtaidistance/tree/v2.0.0</dc:relation>
  <dc:relation>doi:10.5281/zenodo.1202378</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:title>wannesm/dtaidistance v2.0.0</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>software</dc:type>
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