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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 311.4 kB | linux-64/dtw-python-1.3.1-py312h98912ed_0.conda  1 year and 6 months ago 2034 main
conda 320.9 kB | linux-64/dtw-python-1.3.1-py38h01eb140_0.conda  1 year and 6 months ago 1581 main
conda 323.2 kB | linux-64/dtw-python-1.3.1-py311h459d7ec_0.conda  1 year and 6 months ago 2006 main
conda 320.8 kB | linux-64/dtw-python-1.3.1-py310h2372a71_0.conda  1 year and 6 months ago 1659 main
conda 320.7 kB | linux-64/dtw-python-1.3.1-py39hd1e30aa_0.conda  1 year and 6 months ago 1580 main

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