(
    subject,
    dataset="001-2014",
    path=None,
    force_update=False,
    update_path=None,
    base_url=BNCI_URL,
    verbose=None,
)
return dataset_list[dataset](
        subject, path, force_update, update_path, baseurl_list[dataset], verbose
    )
Get paths to local copies of a BNCI dataset files.

    This will fetch data for a given BNCI dataset. Report to the bnci website
    for a complete description of the experimental setup of each dataset.

    Parameters
    ----------
    subject : int
        The subject to load.
    dataset : string
        The bnci dataset name.
    path : None | str
        Location of where to look for the BNCI data storing location.
        If None, the environment variable or config parameter
        ``MNE_DATASETS_BNCI_PATH`` is used. If it doesn't exist, the
        "~/mne_data" directory is used. If the BNCI 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_BNCI_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 :func:`mne.verbose`
        and :ref:`Logging documentation <tut_logging>` for more).

    Returns
    -------
    raws : list
        List of raw instances for each non consecutive recording. Depending
        on the dataset it could be a BCI run or a different recording session.
    event_id: dict
        dictonary containing events and their code.
Get paths to local copies of a BNCI dataset files.
Get paths to local copies of a BNCI dataset files .
def load_data(
    subject,
    dataset="001-2014",
    path=None,
    force_update=False,
    update_path=None,
    base_url=BNCI_URL,
    verbose=None,
):  # noqa: D301
    """Get paths to local copies of a BNCI dataset files.

    This will fetch data for a given BNCI dataset. Report to the bnci website
    for a complete description of the experimental setup of each dataset.

    Parameters
    ----------
    subject : int
        The subject to load.
    dataset : string
        The bnci dataset name.
    path : None | str
        Location of where to look for the BNCI data storing location.
        If None, the environment variable or config parameter
        ``MNE_DATASETS_BNCI_PATH`` is used. If it doesn't exist, the
        "~/mne_data" directory is used. If the BNCI 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_BNCI_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 :func:`mne.verbose`
        and :ref:`Logging documentation <tut_logging>` for more).

    Returns
    -------
    raws : list
        List of raw instances for each non consecutive recording. Depending
        on the dataset it could be a BCI run or a different recording session.
    event_id: dict
        dictonary containing events and their code.
    """
    dataset_list = {
        "001-2014": _load_data_001_2014,
        "002-2014": _load_data_002_2014,
        "004-2014": _load_data_004_2014,
        "008-2014": _load_data_008_2014,
        "009-2014": _load_data_009_2014,
        "001-2015": _load_data_001_2015,
        "003-2015": _load_data_003_2015,
        "004-2015": _load_data_004_2015,
        "009-2015": _load_data_009_2015,
        "010-2015": _load_data_010_2015,
        "012-2015": _load_data_012_2015,
        "013-2015": _load_data_013_2015,
    }

    baseurl_list = {
        "001-2014": BNCI_URL,
        "002-2014": BNCI_URL,
        "001-2015": BNCI_URL,
        "004-2014": BNCI_URL,
        "008-2014": BNCI_URL,
        "009-2014": BNCI_URL,
        "003-2015": BNCI_URL,
        "004-2015": BNCI_URL,
        "009-2015": BBCI_URL,
        "010-2015": BBCI_URL,
        "012-2015": BBCI_URL,
        "013-2015": BNCI_URL,
    }

    if dataset not in dataset_list.keys():
        raise ValueError(
            "Dataset '%s' is not a valid BNCI dataset ID. "
            "Valid dataset are %s." % (dataset, ", ".join(dataset_list.keys()))
        )

    return dataset_list[dataset](
        subject, path, force_update, update_path, baseurl_list[dataset], verbose
    )
def load_data ( subject , dataset = "001-2014" , path = None , force_update = False , update_path = None , base_url = BNCI_URL , verbose = None , ) : # noqa: D301 dataset_list = { "001-2014" : _load_data_001_2014 , "002-2014" : _load_data_002_2014 , "004-2014" : _load_data_004_2014 , "008-2014" : _load_data_008_2014 , "009-2014" : _load_data_009_2014 , "001-2015" : _load_data_001_2015 , "003-2015" : _load_data_003_2015 , "004-2015" : _load_data_004_2015 , "009-2015" : _load_data_009_2015 , "010-2015" : _load_data_010_2015 , "012-2015" : _load_data_012_2015 , "013-2015" : _load_data_013_2015 , } baseurl_list = { "001-2014" : BNCI_URL , "002-2014" : BNCI_URL , "001-2015" : BNCI_URL , "004-2014" : BNCI_URL , "008-2014" : BNCI_URL , "009-2014" : BNCI_URL , "003-2015" : BNCI_URL , "004-2015" : BNCI_URL , "009-2015" : BBCI_URL , "010-2015" : BBCI_URL , "012-2015" : BBCI_URL , "013-2015" : BNCI_URL , } if dataset not in dataset_list . keys ( ) : raise ValueError ( "Dataset '%s' is not a valid BNCI dataset ID. " "Valid dataset are %s." % ( dataset , ", " . join ( dataset_list . keys ( ) ) ) ) return dataset_list [ dataset ] ( subject , path , force_update , update_path , baseurl_list [ dataset ] , verbose )