Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

Appearance settings

NirLab-TAU/sleepeegpy

Open more actions menu

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Logo

sleepeegpy is a high-level package built on top of MNE-python, yasa, PyPREP and specparam (fooof) for preprocessing, analysis, and visualization of sleep EEG data.

The repository also includes a Jupyter notebook demonstrating how to use this package and provides a ready-made workflow for common use cases. image

Installation

Prerequisites

  • Python Version: Ensure you have Python version >3.9 and <3.12 installed.

Steps

  1. Create a Python Virtual Environment: Create a Python virtual environment. For more information you can refer to python venv, virtualenv or conda.
  2. Activate the Environment
  3. Install sleepeegpy:
    pip install sleepeegpy
  4. Download notebooks: Download this repository zip folder, you will need only the notebooks folder.

Quickstart

The notebooks are useful for familiarizing yourself with the library's functionalities. To use them:

  1. Navigate to the Pipeline Notebooks folder and run Jupyter.
    jupyter notebook
  2. Open the complete_pipeline notebook using Jupyter Notebook within the activated environment and follow the instructions.

Additionally, detailed documentation is available for further reference.

RAM requirements

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.

Citation

Morty Proxy This is a proxified and sanitized view of the page, visit original site.