sleepeegpy is a high-level package built on top of mne-python, yasa and specparam (fooof) for preprocessing, analysis and visualisation of sleep EEG data.
- Make sure you have Python version installed. Requires Python >3.9, <3.12.
- Create a Python virtual environment, for more info you can refer to python venv, virtualenv or conda.
- Activate the environment
-
pip install sleepeegpy - Download notebooks.
- Open the complete pipeline notebook in the created environment.
- Follow the notebook's instructions.
For overnight, high density (256 channels) EEG recordings downsampled to 250 Hz expect at least 64 GB RAM expenditure for cleaning, spectral analyses and event detection.
odie = pooch.create(
path=pooch.os_cache("sleepeegpy_dataset"),
base_url="doi:10.5281/zenodo.10362189",
)
odie.load_registry_from_doi()
bad_channels = odie.fetch("bad_channels.txt")
annotations = odie.fetch("annotations.txt")
path_to_eeg = odie.fetch("resampled_raw.fif")
for i in range(1,4):
odie.fetch(f"resampled_raw-{i}.fif")