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Dynamic Time Warping (DTW) algorithm with an O(N) time and memory complexity.

Project description

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.

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Filename, size & hash SHA256 hash help File type Python version Upload date
fastdtw-0.3.2.tar.gz (118.4 kB) Copy SHA256 hash SHA256 Source None Jul 16, 2017

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