v0.1.9

Changes

• Replaced the Histogram feature with Histogram mode (#167)

Improvements

• The correlated_features method now supports returning a filtered feature vector (#163)

Documentation

• Set up a Slack community invite (#164)
• Enhanced documentation for the time_series_feature_extraction and get_features_by_domain functions
• Updated the main example notebook on Human Activity Recognition (#159)

v0.1.8

New Features

• Added a new Datasets module with convenient methods to load single-problem datasets (#156)
• Improved the get_features_by_domain method, allowing easier selection of multiple feature domain combinations

Improvements

• Significantly reduced the computational time for the LPCC feature (#153)
• Resolved deprecation issues with SciPy Wavelets by switching to PyWavelets for features that rely on wavelets (#147)
• Renamed the fft_mean_coefficient feature to spectrogram_mean_coefficient for descriptive correctness (#145)

Bugfixes

• Fixed a bug causing a circular import issue (#154)
• Fixed a ResourceWarning when loading the feature configuration file (#152)
• Removed the use of eval (#150)

Documentation

• Major documentation updates, including detailed explanations of the expected input and output data formats

v0.1.7

• New features

  • Implemented the Lempel-Ziv-Complexity in the temporal domain (#146 <https://github.com/fraunhoferportugal/tsfel/pull/146>_)
  • Added the fractal domain with the following features (#144 <https://github.com/fraunhoferportugal/tsfel/pull/144>_):
    • Detrended fluctuation analysis (DFA)
    • Higuchi fractal dimension
    • Hurst exponent
    • Maximum fractal length
    • Multiscale entropy (MSE)
    • Petrosian fractal dimension

• Changes

  • Changed the autocorrelation logic. It now measures the first lag below (1/e) from the ACF (#142 <https://github.com/fraunhoferportugal/tsfel/issues/142>_).

Version 0.1.6

• Changes

  • Feature total energy changed name to average power
  • Features peak to peak, absolute energy and entropy are now classified as statistical

• Bugfixes

  • Fixed a bug on numpy bool usage (#133 <https://github.com/fraunhoferportugal/tsfel/issues/133>_)
  • Fixed a bug on features' header names

• Improvements

  • Correlated features are now computed using absolute value
  • Unit tests improvements
  • Refactoring of some code sections and overall improved stability

v0.2.0-ops

Update unit tests

v0.2.0

Bug fixed on percentile, spectral_kurtosis and spectral_skewness

Version 0.1.5

• Bugfixes

  • Fixed bug on scipy function median_absolute_deviation to median_abs_deviation #128
  • Fixed on pandas function df.append to pd.concat #120

v0.1.4

Version 0.1.4

• Bugfixes

  • Fixed a bug on the progress bar not being displayed if the signal is passed already divided into windows #49
  • Fixed a bug on the distance feature #54
  • Fixed a bug raising zero division in the ECDF slope feature #57
  • Fixed a bug when adding customised features using the JSON
  • Fixed a bug on LPC was returning inconsistent values #58
  • Fixed a bug on normalised autocorrelation #64

• Improvements

  • Refactoring of some code sections and overall improved stability
  • The documentation has been improved and a FAQ section was created
  • The window_splitter parameter is now deprecated. If the user selected a window_size it is assumed that the signal must be divided into windows.
  • Unit tests improvements

• New features

  • Added to return the size of the feature vector from the configuration dictionary #50

v0.1.3

Fixed versions

v0.1.2

Bump to v0.1.2