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.. currentmodule:: braindecode
- Fix padding's device in :class:`braindecode.models.EEGResNet` (:gh:`451` by Pierre Guetschel)
- Fix skorch version issue (:gh:`465` by Marco Zamboni)
- Adding :class:`braindecode.models.EEGInceptionMI` network for motor imagery (:gh:`428` by Cedric Rommel)
- Adding :class:`braindecode.models.ATCNet` network for motor imagery (:gh:`429` by Cedric Rommel)
- Adding to :class:`braindecode.datasets.tuh.TUH` compatibility with version 3.0 of TUH dataset (:gh:`431` by Mohammad Javad D, Bruno Aristimunha, Robin Tibor Schirrmeister, Lukas Gemein, Denis A. Engemann and Oskar Størmer)
- Adding :class:`braindecode.models.DeepSleepNet` network for sleep staging (:gh:`417` by `Théo Gnassounou`_)
- Fixing conda env in the CI (:gh:`461` by Bruno Aristimunha)
- Fixing E231 missing whitespace after ',' untraceable error in old flake8 (:gh:`460` by Bruno Aristimunha)
- Removing deprecation warning due to torch transposition in :func:`braindecode.augmentation.functional._frequency_shift` (:gh:`446` by Matthieu Terris)
- Renaming the :class:`braindecode.models.EEGInception` network as :class:`braindecode.models.EEGInceptionERP` (:gh:`428` by Cedric Rommel)
- Adding EEG-Inception Network :class:`braindecode.models.EEGInception` (:gh:`390` by Bruno Aristimunha and Cedric Rommel)
- Adding EEG-ITNet Network :class:`braindecode.models.EEGITNet` (:gh:`400` by Ghaith Bouallegue)
- Allowing target_names as list for BaseDataset (:gh:`371` by Mohammad Javad D and Robin Tibor Schirrmeister)
- Adding tutorial with GridSearchCV for data augmentation on the BCIC IV 2a with module braindecode.augmentation (:gh:`389` by Bruno Aristimunha and Cedric Rommel)
- Adding tutorial with GridSearchCV to exemplify how to tune hyperparameters, for instance with the learning rate (:gh:`349` by Lukas Gemein and by Bruno Aristimunha)
- Adding tutorial with a Unified Validation sheme (:gh:`378` by Bruno Aristimunha and Martin Wimpff)
- Adding verbose parameter to :func:`braindecode.preprocessing.create_windows_from_events`, :func:`braindecode.preprocessing.create_windows_from_target_channels`, and :func:`braindecode.preprocessing.create_fixed_length_windows` (:gh:`391` by Lukas Gemein)
- Enable augmentation on GPU within :class:`AugmentedDataloader` via a new device parameter (:gh:`406` by Martin Wimpff, Bruno Aristimunha and Cedric Rommel)
- Fixing parameter subject_ids to recoding_ids in TUHAbnormal example (:gh:`402` by Bruno Aristimunha and Lukas Gemein)
- Bug fix :func:`braindecode.augmentation.functional.ft_surrogate` and add option to sample independently per-channel (:gh:`409` by Martin Wimpff and Cedric Rommel)
- Renaming the method get_params to get_augmentation_params in augmentation classes. This makes the Transform module compatible with scikit-learn cloning mechanism (:gh:`388` by Bruno Aristimunha and Alex Gramfort)
- Delaying the deprecation of the preprocessing scale function :func:`braindecode.preprocessing.scale` and updates tutorials where the function were used. (:gh:`413` by Bruno Aristimunha)
- Removing deprecated functions and classes :func:`braindecode.preprocessing.zscore`, :class:`braindecode.datautil.MNEPreproc` and :class:`braindecode.datautil.NumpyPreproc` (:gh:`415` by Bruno Aristimunha)
- Setting iterator_train__drop_last=True by default for :class:`braindecode.EEGClassifier` and :class:`braindecode.EEGRegressor` (:gh:`411` by Robin Tibor Schirrmeister)
- Adding :class:`braindecode.samplers.SequenceSampler` along with support for returning sequences of windows in :class:`braindecode.datasets.BaseConcatDataset` and an updated sleep staging example to show how to train on sequences of windows (:gh:`263` by Hubert Banville)
- Adding Thinker Invariance Network :class:`braindecode.models.TIDNet` (:gh:`170` by Ann-Kathrin Kiessner, Dan Wilson, Henrik Bonsmann, Vytautas Jankauskas)
- Adding a confusion matrix plot generator :func:`braindecode.visualization.plot_confusion_matrix` (:gh:`274` by Ann-Kathrin Kiessner, Dan Wilson, Henrik Bonsmann, Vytautas Jankauskas)
- Adding data :ref:`augmentation_api` module (:gh:`254` by Cedric Rommel, Alex Gramfort and Thomas Moreau)
- Adding Mixup augmentation :class:`braindecode.augmentation.Mixup` (:gh:`254` by Simon Brandt)
- Adding saving of preprocessing and windowing choices in :func:`braindecode.preprocessing.preprocess`, :func:`braindecode.preprocessing.create_windows_from_events` and :func:`braindecode.preprocessing.create_fixed_length_windows` to datasets to facilitate reproducibility (:gh:`287` by Lukas Gemein)
- Adding :func:`braindecode.models.util.aggregate_probas` to perform self-ensembling of predictions with sequence-to-sequence models (:gh:`294` by Hubert Banville)
- Adding :func:`braindecode.training.scoring.predict_trials` to generate trialwise predictions after cropped training (:gh:`312` by Lukas Gemein)
- Preprocessing and windowing choices are now saved on the level of individual datasets (:gh:`288` by Lukas Gemein)
- Serialization now happens entirely on dataset level creating subsets for individual datasets that contain 'fif' and 'json' files (:gh:`288` Lukas Gemein)
- Instantiation of TUH :class:`braindecode.datasets.tuh.TUH` and TUHAbnormal :class:`braindecode.datasets.tuh.TUHAbnormal`, as well as loading :func:`braindecode.datautil.serialization.load_concat_dataset` of stored datasets now support multiple workers (:gh:`288` by Lukas Gemein)
- Adding balanced sampling of sequences of windows with :class:`braindecode.samplers.BalancedSequenceSampler` as proposed in U-Sleep paper (:gh:`295` by Theo Gnassounou and Hubert Banville)
- :func:`braindecode.preprocessing.preprocess` can now work in parallel and serialize datasets to enable lazy-loading (i.e. preload=False) (:gh:`277` by Hubert Banville)
- Adding :class:`braindecode.models.TimeDistributed` to apply a module on a sequence (:gh:`318` by Hubert Banville)
- Adding time series targets decoding together with :class:`braindecode.datasets.BCICompetitionIVDataset4` and fingers flexion decoding from ECoG examples (:gh:`261` by Maciej Śliwowski and Mohammed Fattouh)
- Make EEGClassifier and EEGRegressor cloneable for scikit-learn (:gh:`347` by Lukas Gemein, Robin Tibor Schirrmeister, Maciej Śliwowski and Alex Gramfort)
- Allow to raise a warning when a few trials are shorter than the windows length, instead of raising an error and stopping all computation. (:gh:`353` by Cedric Rommel)
- Setting torch.backends.cudnn.benchmark in :func:`braindecode.util.set_random_seeds`, adding warning and more info to the docstring to improve reproducibility (:gh:`333` by Maciej Śliwowski)
- Adding option to pass arguments through :class:`braindecode.datasets.MOABBDataset` (:gh:`365` by Pierre Guetschel)
- Adding a possibility to use a dict to split a BaseConcatDataset in :meth:`braindecode.datasets.BaseConcatDataset.split` (:gh:`367` by Alex Gramfort)
- Adding
cropparameter to :class:`braindecode.datasets.SleepPhysionet` dataset to speed up examples (:gh:`367` by Alex Gramfort)
- Correctly computing recording length in :func:`braindecode.preprocessing.windowers.create_fixed_length_windows` in case recording was cropped (:gh:`304` by Lukas Gemein)
- Fixing :class:`braindecode.datasets.SleepPhysionet` to allow serialization and avoid mismatch in channel names attributes (:gh:`327` by Hubert Banville)
- Propagating target_transform to all datasets when using :meth:`braindecode.datasets.BaseConcatDataset.subset` (:gh:`261` by Maciej Śliwowski)
- Removing the default sampling frequency sfreq value in :func:`braindecode.datasets.create_windows_from_events` (:gh:`256` by Ann-Kathrin Kiessner, Dan Wilson, Henrik Bonsmann, Vytautas Jankauskas)
- Made windowing arguments optional in :func:`braindecode.preprocessing.windowers.create_fixed_length_windows` & :func:`braindecode.preprocessing.windowers.create_windows_from_events` (:gh:`269` by Ann-Kathrin Kiessner, Dan Wilson, Henrik Bonsmann, Vytautas Jankauskas)
- Deprecating preprocessing functions :func:`braindecode.preprocessing.zscore` and :func:`braindecode.preprocessing.scale` in favour of sklearn's implementation (:gh:`292` by Hubert Banville)
- :func:`braindecode.preprocessing.preprocess` now returns a :class:`braindecode.dataset.BaseConcatDataset` object (:gh:`277` by Hubert Banville)
- Adding n_jobs parameter to windowers :func:`braindecode.datautil.create_windows_from_events` and :func:`braindecode.datautil.create_fixed_length_windows` to allow for parallelization of the windowing process (:gh:`199` by Hubert Banville)
- Adding support for on-the-fly transforms (:gh:`198` by Hubert Banville)
- Unifying preprocessors under the :class:`braindecode.datautil.Preprocessor` class (:gh:`197` by Hubert Banville)
- Adding self-supervised learning example on the Sleep Physionet dataset along with new sampler module braindecode.samplers (:gh:`178` by Hubert Banville)
- Adding sleep staging example on the Sleep Physionet dataset (:gh:`161` by Hubert Banville)
- Adding new parameters to windowers :func:`braindecode.datautil.create_windows_from_events` and :func:`braindecode.datautil.create_fixed_length_windows` for finer control over epoching (:gh:`152` by Hubert Banville)
- Adding Temporal Convolutional Network :class:`braindecode.models.TCN` (:gh:`138` by Lukas Gemein)
- Adding option to use BaseConcatDataset as input to BaseConcatDataset (:gh:`142` by Lukas Gemein)
- Adding a simplified API for splitting of BaseConcatDataset: parameters property and split_ids in :meth:`braindecode.datasets.BaseConcatDataset.split` are replaced by by (:gh:`147` by Lukas Gemein)
- Adding a preprocessor that realizes a filterbank: :func:`braindecode.datautil.filterbank` (:gh:`158` by Lukas Gemein)
- Removing code duplicate in BaseDataset and WindowsDataset (:gh:`159` by Lukas Gemein)
- Only load data if needed during preprocessing (e.g., allow timecrop without loading) (:gh:`164` by Robin Tibor Schirrmeister)
- Adding option to sort filtered channels by frequency band for the filterbank in :func:`braindecode.datautil.filterbank` (:gh:`185` by Lukas Gemein)
- Adding the USleep model :class:`braindecode.models.USleep` (:gh:`282` by Theo Gnassounou and Omar Chehab)
- Adding :class:`braindecode.models.SleepStagerEldele2021` and :class:`braindecode.models.SleepStagerBlanco2020` models for sleep staging (:gh:`341` by Divyesh Narayanan)
- Amplitude gradients are correctly computed for layers with multiple filters (before, they were accidentally summed over all previous filters in the layer) (:gh:`167` by Robin Tibor Schirrmeister)
- :func:`braindecode.models.get_output_shape` and :func:`braindecode.visualization.compute_amplitude_gradients` assume 3d, not 4d inputs (:gh:`166` by Robin Tibor Schirrmeister)
- Fixing windower functions when the continuous data has been cropped (:gh:`152` by Hubert Banville)
- Fixing incorrect usage of recording ids in TUHAbnormal (:gh:`146` by Lukas Gemein)
- Adding check for correct input dimensions (4d) in TCN (:gh:`169` by Lukas Gemein)
- Fixing :func:`braindecode.datautil.create_windows_from_events` when window_size is not given but there is a
trial_stop_offset_samples(:gh:`148` by Lukas Gemein) - Fixing :meth:`braindecode.classifier.EEGClassifier.predict_proba` and :meth:`braindecode.regressor.EEGRegressor.predict` behavior in the cropped mode (:gh:`171` by Maciej Śliwowski)
- Freeze torch random generator for scoring functions for reproducibility (:gh:`155` by Robin Tibor Schirrmeister)
- Make EEGResNet work for
final_pool_length='auto'(:gh:`223` by Robin Tibor Schirrmeister and Maciej Śliwowski)
- Preprocessor classes :class:`braindecode.datautil.MNEPreproc` and :class:`braindecode.datautil.NumpyPreproc` are deprecated in favor of :class:`braindecode.datautil.Preprocessor` (:gh:`197` by Hubert Banville)
- Parameter stop_offset_samples of :func:`braindecode.datautil.create_fixed_length_windows` must now be set to None instead of 0 to indicate the end of the recording (:gh:`152` by Hubert Banville)