tslearn-team / tslearn-team/tslearn

Global constraints (Sakoe-Chiba/Itakura) for subsequence search

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new feature
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Python
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Description

Is your feature request related to a problem? Please describe.
The method dtw_path accepts one of two optional global constraints (preventing "pathological" matches). However, dtw_subsequence_path doesn't (because the compute mask function assumes two series of equal length).

Describe the solution you'd like
Adding this constraint would be really useful. There is a precedent, the team at UCR has an implementation of DTW subsequence search with a warp window as a fraction of the series length (the source is in C, I think the cost matrix is here). I could try to have a go at this but it might take me a while.

Thanks for all your work on this very useful library!

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Research direction

Start by reading the dtw_path and dtw_subsequence_path entry points, then inspect the compute mask function to understand its equal-length assumption. Compare the requested behavior with the linked UCR implementation and its cost-matrix logic. The work is done when subsequence search accepts the global constraints and constrained paths avoid pathological matches.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

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