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CHANGELOG.md

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Changelog

Version 1.4.1 (19-07-2024)

Added

Changed

Fixed

  • Fixed default CCA in transformers to inv, not pinv

Version 1.4.0 (15-07-2024)

Added

  • Added pinv to utilities
  • Added alpha_x to CCA in tranformers
  • Added alpha_y to CCA in tranformers
  • Added alpha_x to eCCA in classifiers
  • Added alpha_t to eCCA in classifiers
  • Added alpha_x to rCCA in classifiers
  • Added alpha_m to rCCA in classifiers
  • Added squeeze_components to rCCA, eCCA, eTRCA in `classifiers'

Changed

  • Changed numpy typing of np.ndarray to NDArray
  • Changed cca_ and trca_ attributes to be list always in eCCA, rCCA and eTRCA
  • Changed scipy.linalg.inv to pyntbci.utilities.pinv in CCA of transformers
  • Changed decision_function and predict of classifiers to return without additional dimension for components if n_components=1 and squeeze_components=True, both of which are defaults

Fixed

Version 1.3.3 (01-07-2024)

Added

Changed

Fixed

  • Fixed components bug in decision_function of eCCA in classifiers

Version 1.3.2 (23-06-2024)

Added

  • Added cov_estimator_t to eCCA in classifiers

Changed

  • Changed separate covariance estimators for data and templates in eCCA of classifiers

Fixed

Version 1.3.1 (23-06-2024)

Added

Changed

Fixed

  • Fixed zero division eventplot in plotting
  • Fixed event order duration event event_matrix in utilities

Version 1.3.0 (18-06-2024)

Added

  • Removed gating of rCCA in classifiers
  • Removed _score methods in classifiers
  • Added n_components in eCCA in classifiers
  • Added n_components in eTRCA in classifiers

Changed

  • Changed "bes" to "bds" in BayesStopping in stopping in line with publication
  • Changed lx and ly to gamma_x and gamma_y iof eCCA in classifiers
  • Changed gating to gates
  • Changed TRCA in transformers to deal with one-class data only
  • Changed _get_T to get_T in all classifiers

Fixed

Version 1.2.0 (18-04-2024)

Added

Changed

  • Changed lx of rCCA in classifiers to gamma_x, which ranges between 0-1, such that the parameter represents shrinkage regularization
  • Changed ly of rCCA in classifiers to gamma_m, which ranges between 0-1, such that the parameter represents shrinkage regularization
  • Changed lx of CCA in transformers to gamma_x, which ranges between 0-1, such that the parameter represents shrinkage regularization
  • Changed ly of CCA in transformers to gamma_y, which ranges between 0-1, such that the parameter represents shrinkage regularization

Fixed

Version 1.1.0 (17-04-2024)

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

Version 1.0.1 (26-03-2024)

Added

  • Added set_stimulus_amplitudes for rCCA in classifiers

Changed

Fixed

  • Fixed dependency between stimulus and amplitudes in rCCA of classifiers

Version 1.0.0 (22-03-2024)

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

Version 0.2.5 (29-02-2024)

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

Version 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

Version 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

Version 0.2.2

Added

  • Added class TRCA to transformers
  • Added class eTRCA to classifiers
  • Added parameter ensemble to classes in classifiers to allow a separate spatial filter per class

Changed

  • Changed package name from PyNT to PyntBCI to avoid clash with existing pynt library
  • Changed filter order in filterbank of utilities to be optimized given input parameters

Fixed

  • Fixed issue in rCCA of classifiers causing novel events in structure matrix when "cutting cycles"
  • Fixed correlation to not contain mutable input variables

Version 0.2.1

Added

  • Added tests
  • Added tutorials

Changed

  • Changed rCCA to work with non-binary events instead of binary only

Fixed

Version 0.2.0

Added

  • Added dynamic stopping: classes MarginStopping, BetaStopping, and BayesStopping in module stopping
  • Added value inner for variable score_metric in 'classifiers'

Changed

  • Changed all data shapes from (channels, samples, trials) to (trials, channels, samples)
  • Changed all codes shapes from (samples, classes) to (classes, samples)
  • Changed all decision functions to similarity, not distance (e.g., Euclidean), to always maximize

Fixed

  • Fixed zero-mean templates in eCCA and rCCA of classifiers

Version 0.1.0

Added

  • Added Filterbank to classifiers

Changed

  • Changed classifiers all have predict and decision_function methods in classifiers

Fixed

Version 0.0.2

Added

Changed

  • Changed CCA method from sklearn to custom covariance method

Fixed

Version 0.0.1

Added

  • Added eCCA template metrics: average, median, OCSVM
  • Added eCCA spatial filter options: all channels or subset

Changed

Fixed

Version 0.0.0

Added

  • Added CCA in transformers
  • Added rCCA in classifiers
  • Added eCCA in classifier

Changed

Fixed