How to apply/implement Dynamic Time Warping (DTW) or Fast Dynamic Time Warping (FastDTW) in python between 3 or more signals?

Question

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. Fast DTW is a more faster method. I would like to know how to implement this method not only between 2 signals but 3 or more.

distance, warp_path = fastdtw(series2, series1, dist=euclidean)

score 2 · Accepted Answer · answered Feb 17 '21 at 14:21

You essentially need to construct a matrix, evaluating the FastDTW algorithm on all possible combinations of the series.

import fastdtw
import scipy.spatial.distance as sd

def my_fastdtw(sales1, sales2):
    return fastdtw.fastdtw(sales1,sales2)[0]

distance_matrix = sd.pdist(sales, my_fastdtw)

You can see this thread for a reference on how to do it, as well as other possibilities: Efficient pairwise DTW calculation using numpy or cython

How to apply/implement Dynamic Time Warping (DTW) or Fast Dynamic Time Warping (FastDTW) in python between 3 or more signals?

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