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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 299.0 kB | osx-64/dtw-python-1.4.4-py312hbd25219_0.conda  1 year and 18 days ago 298 main
conda 322.0 kB | linux-64/dtw-python-1.4.4-py38hfb59056_0.conda  1 year and 18 days ago 1371 main
conda 321.1 kB | linux-64/dtw-python-1.4.4-py310hc51659f_0.conda  1 year and 18 days ago 1415 main
conda 320.9 kB | linux-64/dtw-python-1.4.4-py39hd3abc70_0.conda  1 year and 18 days ago 1414 main
conda 322.6 kB | linux-64/dtw-python-1.4.4-py311h331c9d8_0.conda  1 year and 18 days ago 1385 main

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