PyBispectra Changelog
Dependencies
- Added support for Python 3.14 in the
conda environment.
Version 1.3.0
Enhancements
- Added support for computing time-resolved bispectral features for the
PAC, WaveShape, General, and Threenorm classes.
- Added
times parameter to the compute() methods of the PAC, PPC, AAC, WaveShape, General, and Threenorm classes to specify time windows for computing time-resolved features over.
- Added support for storing and plotting time-resolved results in the
ResultsCFC, ResultsWaveShape, and ResultsGeneral classes.
- Added
norm parameter to WaveShape.compute() to control normalisation of waveshape results.
- Added
output parameter to compute_tfr() to allow complex coefficients to be returned.
Bug Fixes
- Fixed error where the coupling with
PPC was not being computed correctly.
- Fixed error where
ResultsGeneral.get_results(form="compact") returned complex-valued data as real-valued.
API
- Changed the
data parameter of PPC to require time-frequency representations instead of non-time-resolved Fourier coefficients.
- Increased stringency of data types (real vs. complex) for
data passed to the compute_fft() and compute_tfr() functions, and the PAC, PPC, AAC, WaveShape, TDE, Bispectrum, and Threenorm classes.
Documentation
- Added a new example for computing time-resolved bispectral features.
Version 1.2.4
Bug Fixes
- Fixed error where univariate normalisation of antisymmetrised PAC was not being applied correctly.
Version 1.2.3
Bug Fixes
- Fixed error where NumPy integers and floats were not being recognised as valid types.
Version 1.2.2
Bug Fixes
- Fixed error where
indices in ResultsCFC, ResultsTDE, and ResultsGeneral classes were not being mapped to results correctly.
Documentation
- Improved the warning about invalid frequency combinations returning
np.nan values.
Version 1.2.1
Dependencies
- Added
scikit-learn as a dependency for compatibility with mne>=1.9.
Version 1.2.0
Enhancements
- Added general
Bispectrum and Threenorm classes for computing with flexible kmn channel combinations.
- Added the option to control whether a copy is returned from the
get_results() method of all Results... classes and from SpatioSpectralFilter.get_transformed_data() (default behaviour returns a copy, like in previous versions).
- Added new
fit_ssd(), fit_hpmax(), and transform() methods to the SpatioSpectralFilter class to bring it more in line with scikit-learn fit-transform classes.
Bug Fixes
- Fixed error where the number of subplots exceeding the number of nodes would cause plotting to fail.
- Fixed error where bandpass filter settings for the SSD method in
SpatioSpectralFilter were not being applied correctly.
API
- Changed the default value of
min_ratio in SpatioSpectralFilter.get_transformed_data() from 1.0 to -inf.
Documentation
- Added a new example for computing the bispectrum and threenorm using the general classes.
Version 1.1.0
Enhancements
- Reduced the memory requirement of bispectrum computations.
- Added support for computing & storing time delays of multiple frequency bands simultaneously.
- Added a new option for controlling the colour bar of waveshape plots.
- Added an option for controlling the precision of computations.
Bug Fixes
- Fixed incorrect channel indexing for time delay antisymmetrisation.
API
- Changed how operations on specific frequency/time ranges are specified to be more flexible.
Documentation
- Added a new example for computing time delays on specific frequency bands.
Version 1.0.0