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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 257.0 kB | osx-64/dtw-python-1.1.7-py39h89e85a6_0.tar.bz2  4 years and 2 months ago 201 main
conda 256.6 kB | osx-64/dtw-python-1.1.7-py38h96a0964_0.tar.bz2  4 years and 2 months ago 195 main
conda 269.5 kB | osx-64/dtw-python-1.1.7-py36hfa26744_0.tar.bz2  4 years and 2 months ago 193 main
conda 270.6 kB | linux-64/dtw-python-1.1.7-py37h5e8e339_0.tar.bz2  4 years and 2 months ago 2279 main
conda 280.9 kB | linux-64/dtw-python-1.1.7-py38h497a2fe_0.tar.bz2  4 years and 2 months ago 2285 main
conda 289.6 kB | linux-64/dtw-python-1.1.7-py36h8f6f2f9_0.tar.bz2  4 years and 2 months ago 2372 main
conda 263.4 kB | linux-64/dtw-python-1.1.7-py39h3811e60_0.tar.bz2  4 years and 2 months ago 2900 main

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