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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 11 days ago 297 main
conda 322.0 kB | linux-64/dtw-python-1.4.4-py38hfb59056_0.conda  1 year and 11 days ago 1351 main
conda 321.1 kB | linux-64/dtw-python-1.4.4-py310hc51659f_0.conda  1 year and 11 days ago 1396 main
conda 320.9 kB | linux-64/dtw-python-1.4.4-py39hd3abc70_0.conda  1 year and 11 days ago 1393 main
conda 322.6 kB | linux-64/dtw-python-1.4.4-py311h331c9d8_0.conda  1 year and 11 days ago 1366 main

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