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README.md 2023-06-18 1.3 kB
Release of version 0.13.0 source code.tar.gz 2023-06-18 2.6 MB
Release of version 0.13.0 source code.zip 2023-06-18 2.8 MB
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A new version of pyts is released! The highlights of this release are:

  • Add support for Python 3.10 and 3.11, and drop support for Python 3.7.

  • Update the minimal versions required of the dependencies:

  • NumPy (>= 1.22.4)
  • SciPy (>= 1.8.1)
  • Scikit-Learn (>=1.2.0)
  • Joblib (>=1.1.1)
  • Numba (>=0.55.2)

  • Add an example illustrating time series clustering using pyts.transformation.BOSS transformation with different metrics (by Lucas Plagwitz).

  • Add automatic components-grouping in the Singular Spectrum Analysis for trend-seasonal decomposition with suitable example (by Lucas Plagwitz).

  • Add two new parameters in pyts.decomposition.SingularSpectrumAnalysis: chunksize allows for computing the decomposition of all the input time series using chunks (it should be a bit slower but use less memory), and n_jobs allows for running the decomposition of each chunk in parallel.

  • Set the number of initiations of K-means to compute the initial shapelets in pyts.classification.LearningShapelets: to 10 (to prevent a change of the default value in scikit-learn).

  • Replace base_estimator_ attribute with estimator_ in pyts.classification.TimeSeriesForest and pyts.classification.TSBF (to match the changes made in scikit-learn).

Source: README.md, updated 2023-06-18