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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 16 days ago 1379 main
conda 338.7 kB | osx-64/dtw-python-1.5.1-py311h72ae277_0.conda  1 year and 16 days ago 256 main
conda 352.8 kB | linux-64/dtw-python-1.5.1-py311h331c9d8_0.conda  1 year and 16 days ago 1352 main
conda 348.6 kB | linux-64/dtw-python-1.5.1-py39hd3abc70_0.conda  1 year and 16 days ago 1372 main
conda 349.0 kB | linux-64/dtw-python-1.5.1-py310hc51659f_0.conda  1 year and 16 days ago 1387 main

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