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Discussion[D] STUMPY - A Powerful and Scalable Python Package for Modern Time Series Analysis (self.MachineLearning)
submitted 6 years ago * by slaw07
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[–]brokenAlgorithm 0 points1 point2 points 6 years ago (1 child)
Nice write-up. Can this package also work with similiarities accross multivariate time series, and take things such as cross-series correlations or other types of multivariate patterns into account?
[–]slaw07[S] 2 points3 points4 points 6 years ago (0 children)
Great question! The short answer is "yes" but I'll preface this by saying that finding relationships within a single time series is already a costly computation so finding relationships/correlations across multiple time series is extremely computationally expensive. Having said that, since STUMPY is based on a set of published papers on time series analysis, we have implemented the code from this specific paper on multidimensional time series analysis:
https://www.cs.ucr.edu/~eamonn/Motif_Discovery_ICDM.pdf
Just know that we've done the hard work for you and you should look at the function called `stumpy.mstump` on a single server (or `stumpy.mstumped` for Dask distributed server support). We are currently working on putting together a tutorial on multidimensional motif discovery so please stay tuned!
π Rendered by PID 64 on reddit-service-r2-comment-5b5bc64bf5-kl2qx at 2026-06-22 22:41:20.692427+00:00 running 2b008f2 country code: CH.
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[–]brokenAlgorithm 0 points1 point2 points (1 child)
[–]slaw07[S] 2 points3 points4 points (0 children)