DTW (Dynamic Time Warping)

Comprehensive dynamic time warping module for python.
Documentation is available via ReadTheDocs.

Note: Please consider to use python-dtw package which is compatible with dtw for R.

Installation

pip install dtwalign

Features

Fast computation

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by Numba

Partial alignment

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• before alignment

• after alignment

Local constraint (step pattern)

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example:

| Symmetric2 | AsymmetricP2 | TypeIVc | | :--------------------------: | :----------------------------: | :-----------------------: | | | | |

Global constraint (windowing)

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example:

| Sakoechiba | Itakura | User defined | | :--------------------------: | :-----------------------: | :------------------------: | | | | |

Alignment path visualization

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Usage

see example

Reference

1. Sakoe, H.; Chiba, S., Dynamic programming algorithm optimization for spoken word recognition, Acoustics, Speech, and Signal Processing

• Paolo Tormene, Toni Giorgino, Silvana Quaglini, Mario Stefanelli (2008). Matching Incomplete Time Series with Dynamic Time Warping: An Algorithm and an Application to Post-Stroke Rehabilitation. Artificial Intelligence in Medicine, 45(1), 11-34.

• Toni Giorgino (2009). Computing and Visualizing Dynamic Time Warping Alignments in R: The dtw Package. Journal of Statistical Software, 31(7), 1-24.