mne.datasets.sleep_physionet.age.fetch_data¶
-
mne.datasets.sleep_physionet.age.
fetch_data
(subjects, recording=[1, 2], path=None, force_update=False, update_path=None, base_url='https://physionet.org/physiobank/database/sleep-edfx/sleep-cassette/', verbose=None)[source]¶ Get paths to local copies of PhysioNet Polysomnography dataset files.
This will fetch data from the publicly available subjects from PhysioNet’s study of age effects on sleep in healthy subjects [R008cc7a4bd91-1]_[R008cc7a4bd91-2]_. This corresponds to a subset of 20 subjects, 10 males and 10 females that were 25-34 years old at the time of the recordings. There are two night recordings per subject except for subject 13 since the second record was lost.
See more details in physionet website.
- Parameters
- subjects
list
ofint
The subjects to use. Can be in the range of 0-19 (inclusive).
- recording
list
ofint
The night recording indices. Valid values are : [1], [2], or [1, 2].
- path
None
|str
Location of where to look for the PhysioNet data storing location. If None, the environment variable or config parameter
MNE_DATASETS_PHYSIONET_SLEEP_PATH
is used. If it doesn’t exist, the “~/mne_data” directory is used. If the Polysomnography dataset is not found under the given path, the data will be automatically downloaded to the specified folder.- force_updatebool
Force update of the dataset even if a local copy exists.
- update_pathbool |
None
If True, set the MNE_DATASETS_EEGBCI_PATH in mne-python config to the given path. If None, the user is prompted.
- verbosebool,
str
,int
, orNone
If not None, override default verbose level (see
mne.verbose()
and Logging documentation for more).
- subjects
- Returns
- paths
list
List of local data paths of the given type.
- paths
Notes
For example, one could do:
>>> from mne.datasets import sleep_physionet >>> sleep_physionet.age.fetch_data(subjects=[0]) # doctest: +SKIP
This would download data for subject 0 if it isn’t there already.
References
- 1
MS Mourtazaev, B Kemp, AH Zwinderman, HAC Kamphuisen. Age and gender affect different characteristics of slow waves in the sleep EEG. Sleep 18(7):557–564 (1995).
- 2
Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PCh, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE. (2000) PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation 101(23):e215-e220