eegunity 0.8.2

An open source Python pacakge for large-scale EEG datasets processing

Overview

EEGUnity is a Python package for unified parsing, preprocessing, and export of large-scale EEG datasets.

For project background, see the paper: EEGUnity: Open-Source Tool in Facilitating Unified EEG Datasets Towards Large-Scale EEG Model

Project Documentation

• Online manual (API + tutorials): Read the docs

Usage in Python Project

1. Create a Python Environment

Use Python 3.6 or higher. Python 3.13 is currently not supported due to dependency compatibility limits.

2. Install EEGUnity

pip install eegunity

3. Import EEGUnity

from eegunity import UnifiedDataset

Tutorial Navigation

Core Tutorials

1. How does EEGUnity support multi-modal data: Open
2. How to Format Channel Name and Inspect Metadata: Open
3. How to Make Standard Datasets: Open
4. How to Process Data and Export as h5Dataset: Open
5. How to Read h5Dataset: Open

Advanced Tutorials

1. How to Speed Up with Multithread: Open
2. How to Process Data Using Multiple Computers with EEGUnity: Open
3. How to Reading Rich Meta Data via Kernel: Open
4. How to Parse Non-standard Data Formats: Open
5. How to Build File Hash and File Size Metadata: Open