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wannesm/dtaidistance v2.0.0

Wannes Meert; Kilian Hendrickx; Toon Van Craenendonck


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    <subfield code="a">&lt;p&gt;New in v2:&lt;/p&gt;

&lt;ul&gt;
	&lt;li&gt;Numpy is now an optional dependency, also to compile the C library (only Cython is required).&lt;/li&gt;
	&lt;li&gt;Small optimizations throughout the C code to improve speed.&lt;/li&gt;
	&lt;li&gt;The consistent use of &lt;code&gt;size_t&lt;/code&gt; instead of &lt;code&gt;int&lt;/code&gt; allows for larger data structures on 64 bit machines and be more compatible with Numpy.&lt;/li&gt;
	&lt;li&gt;The parallelization is now implemented directly in C (included if OpenMP is installed).&lt;/li&gt;
	&lt;li&gt;The &lt;code&gt;max_dist&lt;/code&gt; argument turned out to be similar to Silva and Batista&amp;#39;s work on PrunedDTW [7]. The toolbox now implements a version that is equal to PrunedDTW since it prunes more partial distances. Additionally, a &lt;code&gt;use_pruning&lt;/code&gt; argument is added to automatically set &lt;code&gt;max_dist&lt;/code&gt; to the Euclidean distance, as suggested by Silva and Batista, to speed up the computation (a new method &lt;code&gt;ub_euclidean&lt;/code&gt; is available).&lt;/li&gt;
	&lt;li&gt;Support in the C library for multi-dimensional sequences in the &lt;code&gt;dtaidistance.dtw_ndim&lt;/code&gt; package.&lt;/li&gt;
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