mne.datasets.eegbci.
load_data
(subject, runs, path=None, force_update=False, update_path=None, base_url='http://www.physionet.org/physiobank/database/eegmmidb/', verbose=None)[source]¶Get paths to local copies of EEGBCI dataset files.
This will fetch data for the EEGBCI dataset [1], which is also available at PhysioNet [2].
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Notes
For example, one could do:
>>> from mne.datasets import eegbci
>>> eegbci.load_data(1, [4, 10, 14], os.getenv('HOME') + '/datasets') # doctest:+SKIP
This would download runs 4, 10, and 14 (hand/foot motor imagery) runs from subject 1 in the EEGBCI dataset to the ‘datasets’ folder, and prompt the user to save the ‘datasets’ path to the mne-python config, if it isn’t there already.
References
[1] | (1, 2) Schalk, G., McFarland, D.J., Hinterberger, T., Birbaumer, N., Wolpaw, J.R. (2004) BCI2000: A General-Purpose Brain-Computer Interface (BCI) System. IEEE TBME 51(6):1034-1043 |
[2] | (1, 2) Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PCh, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE. (2000) PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation 101(23):e215-e220 |
mne.datasets.eegbci.load_data
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