Pyntbci

Latest version: v1.8.1

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1.1.0

Added

- Added `envelope` module containing `envelope_gammatone` and `envelope_rms` functions
- Added `CriterionStopping` to `stopping` for some static stopping methods

Changed

- Changed default value of `encoding_length` in `rCCA` of `classifiers` of 0.3 to None, which is equivalent to 1 / fs

Fixed

- Fixed variable `fs` of type np.ndarray instead of int in examples, tutorials, and pipelines
- Fixed double call to `decoding_matrix` in `fit` of `rCCA` in `classifiers`

1.0.1

Added

- Added `set_stimulus_amplitudes` for `rCCA` in `classifiers`

Changed

Fixed

- Fixed dependency between `stimulus` and `amplitudes` in `rCCA` of `classifiers`

1.0.0

Added

- Added variable `decoding_length` of `rCCA` in `classifier` controlling the length of a learned spectral filter
- Added variable `decoding_stride` of `rCCA` in `classifier` controlling the stride of a learned spectral filter
- Added function `decoding_matrix` in `utilities` to phase-shit the EEG data maintaining channel-prime ordering
- Added variable `encoding_stride` of `rCCA` in `classifier` controlling the stride of a learned temporal response
- Added module `gating` with gating functions, for instance for multi-component or filterbank analysis
- Added variable `gating` of `rCCA` in `classifier` to deal with multiple CCA components
- Added variable `gating` of `Ensemble` in `classifier`, for example to deal with a filterbank

Changed

- Changed variable `codes` of `rCCA` in `classifiers` to `stimulus`
- Changed variable `transient_size` of `rCCA` in `classifiers` to `encoding_length`
- Changed class `FilterBank` in `classifiers` to `Ensemble`
- Changed function `structure_matrix` in `utilities` to `encoding_matrix`

Fixed

- Fixed several documentation issues

0.2.5

Added

- Added function `eventplot` in `plotting` to visualize an event matrix
- Added variable `running` of `covariance` in `utilities` to do incremental running covariance updates
- Added variable `running` of `CCA` in `transformers` to use a running covariance for CCA
- Added variable `cov_estimator_x` and `cov_estimator_m` of `rCCA` in `classifiers` to change the covariance estimator
- Added event definitions "on", "off" and "onoff" for `event_matrix` in `utilities`

Changed

- Changed the CCA optimization to contain separate computations for Cxx, Cyy and Cxy
- Changed the CCA to allow separate BaseEstimators for Cxx and Cyy

Fixed

- Fixed zero-division in `itr` in `utilities`

0.2.4

Added

- Added CCA cumulative/incremental average and covariance
- Added `amplitudes` (e.g. envelopes) in `structure_matrix` of `utilities`
- Added `max_time` to classes in `stopping` to allow a maximum stopping time for stopping methods
- Added brainamp64.loc to capfiles
- Added plt.show() in all examples

Changed

Fixed

0.2.3

Added

Changed

- Changed example pipelines to include more examples and explanation
- Changed tutorial pipelines to include more examples and explanation

Fixed

- Fixed several documentation issues

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