https://github.com/slaypni/fastdtw

A Python implementation of FastDTW
https://github.com/slaypni/fastdtw

Last synced: 10 days ago
JSON representation

A Python implementation of FastDTW

• Host: GitHub
• URL: https://github.com/slaypni/fastdtw
• Owner: slaypni
• License: mit
• Created: 2015-03-06T13:11:15.000Z (over 9 years ago)
• Default Branch: master
• Last Pushed: 2023-05-19T07:32:43.000Z (over 1 year ago)
• Last Synced: 2024-10-24T16:16:59.438Z (15 days ago)
• Language: Python
• Homepage:
• Size: 253 KB
• Stars: 786
• Watchers: 17
• Forks: 122
• Open Issues: 37
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

Awesome Lists containing this project

• StarryDivineSky - slaypni/fastdtw

README

        
fastdtw

-------

Python implementation of `FastDTW

`_ [1]_, which is an approximate Dynamic Time Warping (DTW) algorithm that provides optimal or near-optimal alignments with an O(N) time and memory complexity.

Install

-------

::

  pip install fastdtw

Example

-------

::

  

  import numpy as np

  from scipy.spatial.distance import euclidean

  from fastdtw import fastdtw

  x = np.array([[1,1], [2,2], [3,3], [4,4], [5,5]])

  y = np.array([[2,2], [3,3], [4,4]])

  distance, path = fastdtw(x, y, dist=euclidean)

  print(distance)

References

----------

.. [1] Stan Salvador, and Philip Chan. "FastDTW: Toward accurate dynamic time warping in linear time and space." Intelligent Data Analysis 11.5 (2007): 561-580.