mne.datasets.fetch_dataset

mne.datasets.fetch_dataset(dataset_params, processor=None, path=None, force_update=False, update_path=True, download=True, check_version=False, return_version=False, accept=False, auth=None, token=None)[source]

Fetch an MNE-compatible dataset.

Parameters
dataset_paramslist of dict | dict

The dataset name(s) and corresponding parameters to download the dataset(s). The dataset parameters that contains the following keys: archive_name, url, folder_name, hash, config_key (optional). See Notes.

processorNone | “unzip” | “untar” | instance of pooch.Unzip | instance of pooch.Untar

What to do after downloading the file. "unzip" and "untar" will decompress the downloaded file in place; for custom extraction (e.g., only extracting certain files from the archive) pass an instance of pooch.Unzip or pooch.Untar. If None (the default), the files are left as-is.

pathNone | str

Directory in which to put the dataset. If None, the dataset location is determined by first checking whether dataset_params['config_key'] is defined, and if so, whether that config key exists in the MNE-Python config file. If so, the configured path is used; if not, the location is set to the value of the MNE_DATA config key (if it exists), or ~/mne_data otherwise.

force_updatebool

Force update of the dataset even if a local copy exists. Default is False.

update_pathbool | None

If True (default), set the mne-python config to the given path. If None, the user is prompted.

downloadbool

If False and the dataset has not been downloaded yet, it will not be downloaded and the path will be returned as '' (empty string). This is mostly used for testing purposes and can be safely ignored by most users.

check_versionbool

Whether to check the version of the dataset or not. Each version of the dataset is stored in the root with a version.txt file.

return_versionbool

Whether or not to return the version of the dataset or not. Defaults to False.

acceptbool

Some MNE-supplied datasets require acceptance of an additional license. Default is False.

authtuple | None

Optional authentication tuple containing the username and password/token, passed to pooch.HTTPDownloader (e.g., auth=('foo', 012345)).

tokenstr | None

Optional authentication token passed to pooch.HTTPDownloader.

Returns
data_pathstr

The path to the fetched dataset.

versionstr

Only returned if return_version is True.

See also

mne.get_config
mne.set_config
mne.datasets.has_dataset

Notes

The dataset_params argument must contain the following keys:

  • archive_name: The name of the (possibly compressed) file to download

  • url: URL from which the file can be downloaded

  • folder_name: the subfolder within the MNE_DATA folder in which to

    save and uncompress (if needed) the file(s)

  • hash: the cryptographic hash type of the file followed by a colon and

    then the hash value (examples: “sha256:19uheid…”, “md5:upodh2io…”)

  • config_key (optional): key passed to mne.set_config() to store

    the on-disk location of the downloaded dataset (e.g., "MNE_DATASETS_EEGBCI_PATH"). This will only work for the provided datasets listed here; do not use for user-defined datasets.

An example would look like:

{'dataset_name': 'sample',
 'archive_name': 'MNE-sample-data-processed.tar.gz',
 'hash': 'md5:12b75d1cb7df9dfb4ad73ed82f61094f',
 'url': 'https://osf.io/86qa2/download?version=5',
 'folder_name': 'MNE-sample-data',
 'config_key': 'MNE_DATASETS_SAMPLE_PATH'}

For datasets where a single (possibly compressed) file must be downloaded, pass a single dict as dataset_params. For datasets where multiple files must be downloaded and (optionally) uncompressed separately, pass a list of dicts.

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Datasets

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mne.datasets.has_dataset