[Java-ML-support] JavaML and Dynamic Time Warping (DTW) confusion

[<je...@hi...>]

Hi,

I need an implementation of calculating the DTW (dynamic time warping)
distance of timeseries patterns in order to compare and classify them.
At this time, the patterns are double[] arrays which is no problem since
I can make them to timeseries objects.

In JavaML I found two implementations of DTW now I'm quite confused. The
two variations in JavaML package are:

--
DTW.getWarpDistBetween(TimeSeries tsI, TimeSeries tsJ);
--

and

--
DTWSimilarity dtw = new DTWSimilarity();
dtw.measure(Instance i1, Instance i2);
--

I looked into source code and the two functions getWarpDistBetween() and
measure() look quite different. In measure() there is a hint that it
maps the dtw distance with f(x)= 1 - (x / (1 + x)) to a similarity
measure. But when I apply this formula to the output of
getWarpDistBetween() it does not provide the same solution.

Could you tell me, whats the difference of these two functions apart
from comversation to a similarity measure in measure()? And which
approach should I choose, if I want a classical dtw distance for two
timeseries?

Thank you in advance!

Best regards,
Jens