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A comprehensive implementation of dynamic time warping (DTW) algorithms in Python. DTW computes the optimal (least cumulative distance) alignment between points of two time series. Common DTW variants covered include local (slope) and global (window) constraints, subsequence matches, arbitrary distance definitions, normalizations, minimum variance matching, and so on. Provides cumulative distances, alignments, specialized plot styles, etc.

copied from cf-staging / dtw-python
Type Size Name Uploaded Downloads Labels
conda 349.1 kB | linux-64/dtw-python-1.5.1-py38hfb59056_0.conda  1 year and 1 month ago 1415 main
conda 338.7 kB | osx-64/dtw-python-1.5.1-py311h72ae277_0.conda  1 year and 1 month ago 257 main
conda 352.8 kB | linux-64/dtw-python-1.5.1-py311h331c9d8_0.conda  1 year and 1 month ago 1389 main
conda 348.6 kB | linux-64/dtw-python-1.5.1-py39hd3abc70_0.conda  1 year and 1 month ago 1409 main
conda 349.0 kB | linux-64/dtw-python-1.5.1-py310hc51659f_0.conda  1 year and 1 month ago 1422 main

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