/dtwalign

Comprehensive dynamic time warping module for python

Primary LanguagePythonMIT LicenseMIT

DTW (Dynamic Time Warping)

Documentation Status

cicd workflow

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

  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.