To be honest, fastdtw is not fast at all
from cdtw import pydtwfrom dtaidistance import dtwfrom fastdtw import fastdtwfrom scipy.spatial.distance import euclideans1=np.array([1,2,3,4],dtype=np.double)s2=np.array([4,3,2,1],dtype=np.double)%timeit dtw.distance_fast(s1, s2)4.1 µs ± 28.6 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)%timeit d2 = pydtw.dtw(s1,s2,pydtw.Settings(step = 'p0sym', window = 'palival', param = 2.0, norm = False, compute_path = True)).get_dist()45.6 µs ± 3.39 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)%timeit d3,_=fastdtw(s1, s2, dist=euclidean)901 µs ± 9.95 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)fastdtw is 219 times slower than dtaidistance lib and 20x slower than cdtw
Consider changing. Here is dtaidistance git:
https://github.com/wannesm/dtaidistance
To install, just:
pip install dtaidistance