johannfaouzi/pyts: Release of version 0.13.0

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)