针对pulse-transit的工具

dist/client/mne/datasets/hf_sef/hf_sef.py

@@ -0,0 +1,87 @@
+#!/usr/bin/env python2
+
+# Authors: The MNE-Python contributors.
+# License: BSD-3-Clause
+# Copyright the MNE-Python contributors.
+
+
+import os
+import os.path as op
+
+from ...utils import _check_option, verbose
+from ..config import MNE_DATASETS
+from ..utils import _do_path_update, _download_mne_dataset, _get_path
+
+
+@verbose
+def data_path(
+    dataset="evoked", path=None, force_update=False, update_path=True, *, verbose=None
+):
+    """Get path to local copy of the high frequency SEF dataset.
+
+    Gets a local copy of the high frequency SEF MEG dataset
+    :footcite:`NurminenEtAl2017`.
+
+    Parameters
+    ----------
+    dataset : 'evoked' | 'raw'
+        Whether to get the main dataset (evoked, structural and the rest) or
+        the separate dataset containing raw MEG data only.
+    path : None | str
+        Where to look for the HF-SEF data storing location.
+        If None, the environment variable or config parameter
+        ``MNE_DATASETS_HF_SEF_PATH`` is used. If it doesn't exist, the
+        "~/mne_data" directory is used. If the HF-SEF 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_HF_SEF_PATH in mne-python
+        config to the given path. If None, the user is prompted.
+    %(verbose)s
+
+    Returns
+    -------
+    path : str
+        Local path to the directory where the HF-SEF data is stored.
+
+    References
+    ----------
+    .. footbibliography::
+    """
+    _check_option("dataset", dataset, ("evoked", "raw"))
+    if dataset == "raw":
+        data_dict = MNE_DATASETS["hf_sef_raw"]
+        data_dict["dataset_name"] = "hf_sef_raw"
+    else:
+        data_dict = MNE_DATASETS["hf_sef_evoked"]
+        data_dict["dataset_name"] = "hf_sef_evoked"
+    config_key = data_dict["config_key"]
+    folder_name = data_dict["folder_name"]
+
+    # get download path for specific dataset
+    path = _get_path(path=path, key=config_key, name=folder_name)
+    final_path = op.join(path, folder_name)
+    megdir = op.join(final_path, "MEG", "subject_a")
+    has_raw = (
+        dataset == "raw"
+        and op.isdir(megdir)
+        and any("raw" in filename for filename in os.listdir(megdir))
+    )
+    has_evoked = dataset == "evoked" and op.isdir(op.join(final_path, "subjects"))
+    # data not there, or force_update requested:
+    if has_raw or has_evoked and not force_update:
+        _do_path_update(path, update_path, config_key, folder_name)
+        return final_path
+
+    # instantiate processor that unzips file
+    data_path = _download_mne_dataset(
+        name=data_dict["dataset_name"],
+        processor="untar",
+        path=path,
+        force_update=force_update,
+        update_path=update_path,
+        download=True,
+    )
+    return data_path