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
by Numba
Partial alignment
- before alignment
- after alignment
Local constraint (step pattern)
example:
| Symmetric2 | AsymmetricP2 | TypeIVc |
|---|---|---|
 |
 |
 |
Global constraint (windowing)
example:
| Sakoechiba | Itakura | User defined |
|---|---|---|
 |
 |
 |
Alignment path visualization
Usage
see example
Reference
- 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.
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Toni Giorgino (2009). Computing and Visualizing Dynamic Time Warping Alignments in R: The dtw Package. Journal of Statistical Software, 31(7), 1-24.
