myoverse.datasets.supervised.EMGDataset.__init__

EMGDataset.__init__(emg_data_path=PosixPath('REPLACE ME'), emg_data={}, ground_truth_data_path=PosixPath('REPLACE ME'), ground_truth_data={}, ground_truth_data_type='kinematics', sampling_frequency=0.0, tasks_to_use=(), save_path=PosixPath('REPLACE ME'), emg_filter_pipeline_before_chunking=(), emg_representations_to_filter_before_chunking=(), emg_filter_pipeline_after_chunking=(), emg_representations_to_filter_after_chunking=(), ground_truth_filter_pipeline_before_chunking=(), ground_truth_representations_to_filter_before_chunking=(), ground_truth_filter_pipeline_after_chunking=(), ground_truth_representations_to_filter_after_chunking=(), chunk_size=192, chunk_shift=64, testing_split_ratio=0.2, validation_split_ratio=0.2, augmentation_pipelines=(), amount_of_chunks_to_augment_at_once=250, debug_level=0, silence_zarr_warnings=True)

Parameters:

• emg_data_path (Path)

• emg_data (dict[str, ndarray])

• ground_truth_data_path (Path)

• ground_truth_data (dict[str, ndarray])

• ground_truth_data_type (str)

• sampling_frequency (float)

• tasks_to_use (Sequence[str])

• save_path (Path)

• emg_filter_pipeline_before_chunking (list[list[FilterBaseClass]])

• emg_representations_to_filter_before_chunking (list[list[str]])

• emg_filter_pipeline_after_chunking (list[list[FilterBaseClass]])

• emg_representations_to_filter_after_chunking (list[list[str]])

• ground_truth_filter_pipeline_before_chunking (list[list[FilterBaseClass]])

• ground_truth_representations_to_filter_before_chunking (list[list[str]])

• ground_truth_filter_pipeline_after_chunking (list[list[FilterBaseClass]])

• ground_truth_representations_to_filter_after_chunking (list[list[str]])

• chunk_size (int)

• chunk_shift (int)

• testing_split_ratio (float)

• validation_split_ratio (float)

• augmentation_pipelines (list[list[EMGAugmentation]])

• amount_of_chunks_to_augment_at_once (int)

• debug_level (int)

• silence_zarr_warnings (bool)