Dynamic Time Warping

This package provides a Cython implementation of the Dynamic Time Warping algorithm.

This algorithm should easily handle data with lengths up to 10,000 (or more), although memory requirements will eventually impose an upper bound. It has been demonstrated in our testing that this implementation significantly outperforms a pure Python implementation (no surprise there) but is also significantly faster than using the dtw package in R when calling it from Python.

This algorithm is hard-coded to use the symmetric2 step pattern - the default step pattern used by the R algorithm. But feel free to fork and modify if you need another step pattern, the code is very short!

Installation

Being a compiled extension package, we are doing our best to provide compiled versions via conda.

Simply run:

conda install dtw -c freemapa

If conda does not have a package for your architecture (or you are not using conda), you can certainly compile this package yourself.

Simply download the source code and run:

python setup.py install

This will require NumPy and Cython (both common packages).

Calling the algorithm

To call the algorithm, simply import dtw in Python. The algorithm takes two arrays of data (template and query) as inputs and returns four values: distance, alignment1, alignment2, and costs_matrix.

The algorithm is actually quite short, so please give it a quick read if you wish to know more about how it works.