Changelog

Version 0.1.7

  • New features
    • Implemented the Lempel-Ziv-Complexity in the temporal domain (#146)

    • Added the fractal domain with the following features (#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).

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)

    • 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

Version 0.1.5

  • Bugfixes - Fixed a bug on scipy function median_absolute_deviation to median_abs_deviation (#128) - Fixed on pandas function df.append to pd.concat (#120)

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)

Version 0.1.3

  • Bugfixes
    • Bug fixes on computational complexity calculation (#15)

    • Fixed an error on lpcc feature (#38)

    • Removed entropy warning (#38)

  • Improvements
    • Code cleaning on (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)

    • Added progress bar during feature extraction (#16)

    • Implemented multiprocessing. The n_jobs kwarg selects the number of CPUs to be scheduled (#30)

    • Added the neighbourhood_peaks feature

Version 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

Version 0.1.0

  • Release of TSFEL with documentation