pyts.metrics.dtw(x=None, y=None, dist='square', method='fast', options={'radius': 0}, return_cost=False, return_accumulated=False, return_path=False)

Fast Dynamic Time Warping distance.

This version of DTW builds an adaptive constraint region. The constraint region is created recursively by downsampling the time series, computing the optimal path and projecting it to a higher resolution. This process is repeated until the resolution matches the original resolution.

See also

For documentation for the rest of the parameters, see dtw().

radius : int (default = 0)

The radius used to expand the constraint region. The optimal path computed at the resolution level is expanded with radius cells to the top, bottom, left and right of every cell belonging to the optimal path. It is computed at the resolution level.


[1]S. Salvador ans P. Chan, “FastDTW: Toward Accurate Dynamic Time Warping in Linear Time and Space”. KDD Workshop on Mining Temporal and Sequential Data, 70–80 (2004).