moabb.datasets.base.BaseDataset¶
-
class
moabb.datasets.base.
BaseDataset
(subjects, sessions_per_subject, events, code, interval, paradigm, doi=None, unit_factor=1000000.0)[source][source]¶ Parameters required for all datasets
- Parameters
subjects (List of int) – List of subject number (or tuple or numpy array)
sessions_per_subject (int) – Number of sessions per subject (if varying, take minimum)
events (dict of strings) – String codes for events matched with labels in the stim channel. Currently imagery codes codes can include: - left_hand - right_hand - hands - feet - rest - left_hand_right_foot - right_hand_left_foot - tongue - navigation - subtraction - word_ass (for word association)
code (string) – Unique identifier for dataset, used in all plots
interval (list with 2 entries) – Imagery interval as defined in the dataset description
paradigm ([‘p300’,’imagery’, ‘ssvep’]) – Defines what sort of dataset this is
doi (DOI for dataset, optional (for now))
Methods
data_path
(subject[, path, force_update, …])Get path to local copy of a subject data.
download
([subject_list, path, force_update, …])Download all data from the dataset.
get_data
([subjects])Return the data correspoonding to a list of subjects.
-
abstract
data_path
(subject, path=None, force_update=False, update_path=None, verbose=None)[source][source]¶ Get path to local copy of a subject data.
- Parameters
subject (int) – Number of subject to use
path (None | str) – Location of where to look for the data storing location. If None, the environment variable or config parameter
MNE_DATASETS_(dataset)_PATH
is used. If it doesn’t exist, the “~/mne_data” directory is used. If the dataset is not found under the given path, the data will be automatically downloaded to the specified folder.force_update (bool) – Force update of the dataset even if a local copy exists.
update_path (bool | None **Deprecated**) – If True, set the MNE_DATASETS_(dataset)_PATH in mne-python config to the given path. If None, the user is prompted.
verbose (bool, str, int, or None) – If not None, override default verbose level (see
mne.verbose()
).
- Returns
path – Local path to the given data file. This path is contained inside a list of length one, for compatibility.
- Return type
list of str
-
download
(subject_list=None, path=None, force_update=False, update_path=None, accept=False, verbose=None)[source][source]¶ Download all data from the dataset.
This function is only usefull to download all the dataset at once.
- Parameters
subject_list (list of int | None) – List of subjects id to download, if None all subjects are downloaded.
path (None | str) – Location of where to look for the data storing location. If None, the environment variable or config parameter
MNE_DATASETS_(dataset)_PATH
is used. If it doesn’t exist, the “~/mne_data” directory is used. If the dataset is not found under the given path, the data will be automatically downloaded to the specified folder.force_update (bool) – Force update of the dataset even if a local copy exists.
update_path (bool | None) – If True, set the MNE_DATASETS_(dataset)_PATH in mne-python config to the given path. If None, the user is prompted.
accept (bool) – Accept licence term to download the data, if any. Default: False
verbose (bool, str, int, or None) – If not None, override default verbose level (see
mne.verbose()
).
-
get_data
(subjects=None)[source][source]¶ Return the data correspoonding to a list of subjects.
The returned data is a dictionary with the folowing structure:
data = {'subject_id' : {'session_id': {'run_id': raw} } }
subjects are on top, then we have sessions, then runs. A sessions is a recording done in a single day, without removing the EEG cap. A session is constitued of at least one run. A run is a single contigous recording. Some dataset break session in multiple runs.
- Parameters
subjects (List of int) – List of subject number
- Returns
data – dict containing the raw data
- Return type
Dict