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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 297.3 kB | linux-64/dtw-python-1.3.0-py39hb9d737c_0.tar.bz2  2 years and 10 months ago 2220 main
conda 305.2 kB | linux-64/dtw-python-1.3.0-py38h0a891b7_0.tar.bz2  2 years and 10 months ago 1754 main

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