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Software . 2020
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ZENODO
Software . 2020
Data sources: ZENODO
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wannesm/dtaidistance v2.0.0

Authors: Wannes Meert; Kilian Hendrickx; Toon Van Craenendonck;

wannesm/dtaidistance v2.0.0

Abstract

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.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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5
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