braindecode.preprocessing.preprocess#

braindecode.preprocessing.preprocess(concat_ds: BaseConcatDataset, preprocessors: list[Preprocessor], save_dir: str | None = None, overwrite: bool = False, n_jobs: int | None = None, offset: int = 0)[source]#

Apply preprocessors to a concat dataset.

Parameters:

concat_ds (BaseConcatDataset) – A concat of BaseDataset or WindowsDataset datasets to be preprocessed.
preprocessors (list(Preprocessor)) – List of Preprocessor objects to apply to the dataset.
save_dir (str | None) – If a string, the preprocessed data will be saved under the specified directory and the datasets in concat_ds will be reloaded with preload=False.
overwrite (bool) – When save_dir is provided, controls whether to delete the old subdirectories that will be written to under save_dir. If False and the corresponding subdirectories already exist, a FileExistsError will be raised.
n_jobs (int | None) – Number of jobs for parallel execution. See joblib.Parallel for a more detailed explanation.
offset (int) – If provided, the integer is added to the id of the dataset in the concat. This is useful in the setting of very large datasets, where one dataset has to be processed and saved at a time to account for its original position.

Returns: