Tsfel

Latest version: v0.1.9

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0.1.3

=============
- Bugfixes
- Bug fixes on computational complexity calculation (`15 <https://github.com/fraunhoferportugal/tsfel/pull/15>`_)
- Fixed an error on `lpcc` feature (`38 <https://github.com/fraunhoferportugal/tsfel/pull/38>`_)
- Removed `entropy` warning (`38 <https://github.com/fraunhoferportugal/tsfel/pull/38>`_)

- Improvements
- Code cleaning on (`TSFEL_HAR_Example.ipynb <https://github.com/fraunhoferportugal/tsfel/blob/development/notebooks/TSFEL_HAR_Example.ipynb>`_)
- `ecdf` code cleaning and computational optimization
- Overlap value is now optional and set to default as 0
- Unit test improvements
- Nomenclature review of peak-related features

- New features:
- Added new tutorials based on Jupyter notebooks (`19 <https://github.com/fraunhoferportugal/tsfel/issues/19>`_)
- Added progress bar during feature extraction (`16 <https://github.com/fraunhoferportugal/tsfel/issues/16>`_)
- Implemented multiprocessing. The `n_jobs` kwarg selects the number of CPUs to be scheduled (`30 <https://github.com/fraunhoferportugal/tsfel/pull/30>`_)
- Added the `neighbourhood_peaks` feature

0.1.1

=============

- Added new features
- Empirical cumulative distribution function
- Empirical cumulative distribution function percentile
- Empirical cumulative distribution function slope
- Empirical cumulative distribution function percentile count
- Spectral entropy
- Wavelet entropy
- Wavelet absolute mean
- Wavelet standard deviation
- Wavelet variance
- Wavelet energy

- Minor fixes for Google Colab

0.1.0

=============

- Release of TSFEL with documentation

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