metabci.brainda.datasets.cbcic module

China BCI Competition.

class metabci.brainda.datasets.cbcic.CBCIC2019001[source]

Bases: BaseDataset

2019 China BCI competition Dataset for MI in preliminary contest A/B.

Motor imagery dataset from China BCI competition in 2019.

This dataset contains EEG recordings from 18 subjects, performing 2 or 3 tasks of motor imagery (left hand, right hand or feet). Data have been recored at 1000hz with 64 electrodes (59 in use except ECG, HEOR, HEOL, VEOU, VEOL channels) by an neuracle EEG amplifier.

data_path(subject: str | int, path: str | Path | None = None, force_update: bool = False, update_path: bool | None = None, proxies: Dict[str, str] | None = None, verbose: bool | str | int | None = None) → List[List[str | Path]][source]

Get path to local copy of a subject data.

Parameters:

  • subject (Union[str, int]) – subject id

  • path (Optional[Union[str, Path]], optional) – Location of where to look for the data storing location. If None, the environment variable or config parameter MNE_DATASETS_(dataset_code)_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, by default None

  • force_update (bool, optional) – force update of the dataset even if a local copy exists, by default False

  • update_path (Optional[bool], optional) – If True, set the MNE_DATASETS_(dataset)_PATH in mne-python config to the given path. If None, the user is prompted, by default None

  • proxies (Optional[Union[bool, str, int]], optional) – proxies if needed

  • verbose (Optional[Union[bool, str, int]], optional) – [description], by default None

Returns:

local path of a subject data, the first list is session and the second list is run

Return type:

List[List[Union[str, Path]]]

class metabci.brainda.datasets.cbcic.CBCIC2019004[source]

Bases: BaseDataset

2019 China BCI competition Dataset for MI in final competition.

Motor imagery dataset from China BCI competition in 2019.

This dataset contains EEG recordings from 18 subjects, performing 2 or 3 tasks of motor imagery (left hand, right hand or feet). Data have been recored at 1000hz with 64 electrodes (59 in use except ECG, HEOR, HEOL, VEOU, VEOL channels) by an neuracle EEG amplifier.

data_path(subject: str | int, path: str | Path | None = None, force_update: bool = False, update_path: bool | None = None, proxies: Dict[str, str] | None = None, verbose: bool | str | int | None = None) → List[List[str | Path]][source]

Get path to local copy of a subject data.

Parameters:

  • subject (Union[str, int]) – subject id

  • path (Optional[Union[str, Path]], optional) – Location of where to look for the data storing location. If None, the environment variable or config parameter MNE_DATASETS_(dataset_code)_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, by default None

  • force_update (bool, optional) – force update of the dataset even if a local copy exists, by default False

  • update_path (Optional[bool], optional) – If True, set the MNE_DATASETS_(dataset)_PATH in mne-python config to the given path. If None, the user is prompted, by default None

  • proxies (Optional[Union[bool, str, int]], optional) – proxies if needed

  • verbose (Optional[Union[bool, str, int]], optional) – [description], by default None

Returns:

local path of a subject data, the first list is session and the second list is run

Return type:

List[List[Union[str, Path]]]

class metabci.brainda.datasets.cbcic.XuaVEPDataset(paradigm='aVEP')[source]

Bases: BaseTimeEncodingDataset

data_path(subject: str | int, path: str | Path | None = None, force_update: bool = False, update_path: bool | None = None, proxies: Dict[str, str] | None = None, verbose: bool | str | int | None = None)[source]

Get path to local copy of a subject data.

Parameters:

  • subject (Union[str, int]) – subject id

  • path (Optional[Union[str, Path]], optional) – Location of where to look for the data storing location. If None, the environment variable or config parameter MNE_DATASETS_(dataset_code)_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, by default None

  • force_update (bool, optional) – force update of the dataset even if a local copy exists, by default False

  • update_path (Optional[bool], optional) – If True, set the MNE_DATASETS_(dataset)_PATH in mne-python config to the given path. If None, the user is prompted, by default None

  • proxies (Optional[Union[bool, str, int]], optional) – proxies if needed

  • verbose (Optional[Union[bool, str, int]], optional) – [description], by default None

Returns:

local path of a subject data, the first list is session and the second list is run

Return type:

List[List[Union[str, Path]]]