Python extension backed by a multi-threaded Rust implementation of Dynamic Time Warping (DTW).

To install rustDTW, simply:

pip install rust-dtw

In time series analysis, dynamic time warping (DTW) is one of the algorithms for measuring similarity between two temporal sequences, which may vary in speed 1. This has applications in speech recognition, time series classification and neuroscience.

rustDTW was designed for usage with timeseries data from functional brain regions. However any data represented as a numpy matrix can be provided.

import numpy as np
import rust_dtw
  
rust_dtw.dtw(
  s=np.array([0., 1., 2.]), 
  t=np.array([3., 4., 5.]), 
  window=50, 
  distance_mode="euclidean"
  )
>>> 5.0990195

For more examples please see examples/ or explore the wiki.

• PyO3
• Maturin
• rust-numpy
• Rayon

To get started with development, simply clone the repository and edit the main library code in src/. Once done, simply build and test the code with ./build.sh.

git clone https://github.com/FL33TW00D/rustDTW.git
cd rust-dtw/
./build.sh

All tests are implemented using pytest.

poetry run pytest

rustDTW is free and open-source software licensed under the MIT License.