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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 259.5 kB | osx-64/dtw-python-1.1.6-py36h8062767_0.tar.bz2  4 years and 8 months ago 305 main
conda 271.2 kB | linux-64/dtw-python-1.1.6-py38hab2c0dc_0.tar.bz2  4 years and 8 months ago 2541 main
conda 280.5 kB | linux-64/dtw-python-1.1.6-py36h68bb277_0.tar.bz2  4 years and 8 months ago 2506 main
conda 278.0 kB | linux-64/dtw-python-1.1.6-py37h161383b_0.tar.bz2  4 years and 8 months ago 2549 main

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