braindecode.datasets.MOABBDataset¶
- class braindecode.datasets.MOABBDataset(dataset_name, subject_ids)¶
A class for moabb datasets.
- Parameters
- dataset_name: name of dataset included in moabb to be fetched
- subject_ids: list(int) | int
(list of) int of subject(s) to be fetched
- Attributes
- cummulative_sizes
- transform
Methods
Concatenate the metadata and description of the wrapped Epochs.
save(path[, overwrite])Save dataset to files.
split([by, property, split_ids])Split the dataset based on information listed in its description DataFrame or based on indices.
cumsum
- get_metadata()¶
Concatenate the metadata and description of the wrapped Epochs.
- Returns
- pd.DataFrame:
DataFrame containing as many rows as there are windows in the BaseConcatDataset, with the metadata and description information for each window.
- save(path, overwrite=False)¶
Save dataset to files.
- Parameters
- path: str
Directory to which .fif / -epo.fif and .json files are stored.
- overwrite: bool
Whether to delete old files (.json, .fif, -epo.fif) in specified directory prior to saving.
- split(by=None, property=None, split_ids=None)¶
Split the dataset based on information listed in its description DataFrame or based on indices.
- Parameters
- by: str | list(int) | list(list(int))
If by is a string, splitting is performed based on the description DataFrame column with this name. If by is a (list of) list of integers, the position in the first list corresponds to the split id and the integers to the datapoints of that split.
- property: str
Some property which is listed in info DataFrame.
- split_ids: list(int) | list(list(int))
List of indices to be combined in a subset.
- Returns
- splits: dict{str: BaseConcatDataset}
A dictionary with the name of the split (a string) as key and the dataset as value.
