Function _download_all_example_data

mne/datasets/utils.py:329–404

Download all datasets used in examples and tutorials.

(verbose=True)

@verbose
def _download_all_example_data(verbose=True):
    """Download all datasets used in examples and tutorials."""
    # This function is designed primarily to be used by CircleCI, to:
    #
    # 1. Streamline data downloading
    # 2. Make CircleCI fail early (rather than later) if some necessary data
    #    cannot be retrieved.
    # 3. Avoid download statuses and timing biases in rendered examples.
    #
    # verbose=True by default so we get nice status messages.
    # Consider adding datasets from here to CircleCI for PR-auto-build
    import openneuro

    paths = dict()
    for kind in (
        "sample testing misc spm_face somato hf_sef multimodal "
        "fnirs_motor opm mtrf fieldtrip_cmc kiloword phantom_kit phantom_4dbti "
        "refmeg_noise ssvep epilepsy_ecog ucl_opm_auditory eyelink "
        "erp_core brainstorm.bst_raw brainstorm.bst_auditory "
        "brainstorm.bst_resting brainstorm.bst_phantom_ctf "
        "brainstorm.bst_phantom_elekta phantom_kernel"
    ).split():
        mod = importlib.import_module(f"mne.datasets.{kind}")
        data_path_func = getattr(mod, "data_path")
        kwargs = dict()
        if "accept" in inspect.getfullargspec(data_path_func).args:
            kwargs["accept"] = True
        paths[kind] = data_path_func(**kwargs)
        logger.info(f"[done {kind}]")

    # Now for the exceptions:
    from . import (
        eegbci,
        fetch_fsaverage,
        fetch_hcp_mmp_parcellation,
        fetch_infant_template,
        fetch_phantom,
        limo,
        sleep_physionet,
    )

    eegbci.load_data(subjects=1, runs=[6, 10, 14], update_path=True)
    eegbci.load_data(subjects=range(1, 5), runs=[3], update_path=True)
    logger.info("[done eegbci]")

    sleep_physionet.age.fetch_data(subjects=[0, 1], recording=[1])
    logger.info("[done sleep_physionet]")

    # If the user has SUBJECTS_DIR, respect it, if not, set it to the EEG one
    # (probably on CircleCI, or otherwise advanced user)
    fetch_fsaverage(subjects_dir=None)
    logger.info("[done fsaverage]")

    # Now also update the sample dataset path, if not already SUBJECTS_DIR
    # (some tutorials make use of these files)
    fetch_fsaverage(subjects_dir=paths["sample"] / "subjects")

    fetch_infant_template("6mo")