Recent Releases of pyts
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.BOSStransformation 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:chunksizeallows for computing the decomposition of all the input time series using chunks (it should be a bit slower but use less memory), andn_jobsallows 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 withestimator_inpyts.classification.TimeSeriesForestandpyts.classification.TSBF(to match the changes made in scikit-learn).
- Python
Published by johannfaouzi over 2 years ago
pyts - Release of version 0.12.0
A new version of pyts is released! The highlights of this release are:
Add support for Python 3.9 and drop support for Python 3.6.
Add the Time Series Forest algorithm implemented as
pyts.classification.TimeSeriesForest.Add the Time Series Bag-of-Features algorithm implemented as
pyts.classification.TSBF.Replace
scikit-learnmixin classes withpytsmixin classes to have standardized docstrings.Update the examples in the Imaging time series section of the gallery of examples.
Remove some constraints when discretizing time series (number of bins, time series with low variance) that impact the following classes:
pyts.preprocessing.KBinsDiscretizerpyts.approximation.SymbolicAggregateApproximationpyts.bag_of_words.BagOfWordspyts.classification.SAXVSM
Remove specific functions for the different variants of Dynamic Time Warping (all
dtw_*functions), only the mainpyts.metrics.dtwis kept.
- Python
Published by johannfaouzi over 4 years ago
pyts - Release of version 0.11.0
A new version of pyts is released! The highlights of this release are: - Add support for Python 3.8 and drop support for Python 3.5.
Rework the BagOfWords algorithm to match the description of the algorithm in the original paper. The former version of BagOfWords is available as WordExtractor in the
pyts.bag_of_wordsmodule.Update the SAXVSM classifier with the new version of BagOfWords.
Add the BagOfPatterns algorithm in the
pyts.transformationmodule.Add the ROCKET algorithm in the
pyts.transformationmodule.Add the LearningShapelets algorithm in the
pyts.classificationmodule.Deprecated specific functions for Dynamic Time Warping (all
dtw_*functions), only the mainpyts.metrics.dtwis kept.
- Python
Published by johannfaouzi almost 6 years ago
pyts - Release of version 0.10.0
This new version has seen two major updates in the source code: DTW functions now support unequal-length time series and a new parameter has been added for the case where the cost matrix has already been precomputed; the Shapelet Transform algorithm has been added in the transformation module. Continuous integration is now performed on Azure Pipelines instead of Travis and Appveyor. The documentation has been revamped and is much more detailed.
- Python
Published by johannfaouzi about 6 years ago
pyts - pyts 0.7.0
This new release brings a lot of new features. The hierarchy of the code has been changed, with more modules, to make it clearer. Code of already implemented algorithms has been optimized. More algorithms have been implemented.
- Python
Published by johannfaouzi almost 8 years ago