EEGUnity documentation

Contents:

• eegunity
  • eegunity package
    • Subpackages
      • eegunity.modules package
      • eegunity.resources package
      • eegunity.utils package
    • Submodules
    • eegunity.unifieddataset module
      • UnifiedDataset
    • Module contents
• Tutorials
  • EEGUnity: Supporting Multi-Modal Data
    • Special Notes
    • Multimodal Support
    • Custom Batch Processing
    • Recommendations
  • Formatting Channel Names and Inspecting Metadata
    • Requirements
    • Steps
      • Step 1: Load the Dataset
      • Step 2: Save the Initial Locator File
      • Step 3: Select EEG data
      • Step 4: Format Channel Names
      • Step 7: Reload the Dataset
  • Creating a Standardized FIF Dataset using EEGUnity
    • Prerequisites
    • Purpose
    • 🚀 Step 0: Prepare a Python Environment
    • Step 1 Prepare a Python Project
    • Step 2 Make Standard Script for Datasets
    • Detailed Explanation of the Code
    • Key Points to Remember
  • Cooperation with Multiple Computers or Servers using EEGUnity
    • Prerequisites
    • Assumptions
    • For Researcher A
    • For Researcher B
  • EEG Dataset Processing Tutorial
    • Demo 1: Detailed Processing Workflow (demo_make_h5Dataset.py)
      • Key Steps:
      • Code:
    • Demo 2: Quick Batch Processing (demo_make_h5Dataset_quick.py)
      • Key Steps:
      • Code:
  • Reading EEGUnity HDF5 Files: A Guide
    • 1. Introduction
    • 2. What is HDF5?
    • 3. Understanding Data Saving in HDF5
    • 4. Sample Script to Read HDF5 Files
  • Speeding Up EEGUnity Processing with Multithreading
    • 1. Introduction
    • 2. When to Use Multithreading
    • 3. Step-by-Step Guide
      • Step 1: Group Dataset by Domain
      • Step 2: Define the Task Function
      • Step 3: Run Tasks with ThreadPoolExecutor
    • 4. Summary
    • 5. Learn More

Indices and tables

• Index

• Module Index

• Search Page