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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 254.2 kB | osx-arm64/dtw-python-1.1.12-py39h5161555_0.tar.bz2  3 years and 4 months ago 68 main
conda 269.7 kB | osx-64/dtw-python-1.1.12-py37h271585c_0.tar.bz2  3 years and 4 months ago 74 main
conda 272.0 kB | osx-64/dtw-python-1.1.12-py38h96a0964_0.tar.bz2  3 years and 4 months ago 70 main
conda 280.4 kB | linux-ppc64le/dtw-python-1.1.12-py37h6642d69_0.tar.bz2  3 years and 4 months ago 35 main
conda 601.4 kB | linux-64/dtw-python-1.1.12-py39h3811e60_0.tar.bz2  3 years and 4 months ago 2418 main
conda 288.6 kB | linux-64/dtw-python-1.1.12-py37h5e8e339_0.tar.bz2  3 years and 4 months ago 1885 main
conda 276.6 kB | linux-64/dtw-python-1.1.12-py38h497a2fe_0.tar.bz2  3 years and 4 months ago 1827 main

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