🧠 AutoCleanEEG-View

AutoCleanEEG-View is a simple yet powerful tool for neuroscientists, researchers, and EEG enthusiasts to visualize EEG files such as EEGLAB .set, .edf, .bdf, BrainVision .vhdr, EGI .mff/.raw, MNE .fif, and NeuroNexus (.nnx, .nex, via Neo) using the modern MNE-QT Browser.

✨ Features

• Simple Interface: Just one command to view your EEG data
• Interactive Visualization: Pan, zoom, filter, and explore your EEG signals
• Automatic Channel Type Detection: Properly handles EEG, EOG, ECG channels
• Event Markers: View annotations and event markers in your recordings
• Cross-Platform: Works on macOS and Linux
• Extensible Loaders: Each format lives in its own plugin module for easy maintenance

🚀 Quick Start

Installation (uv preferred)

# Using Astral's uv (recommended)
uv pip install autocleaneeg-view

# Or with pip
pip install autocleaneeg-view

Basic Usage

# Canonical command (default opens the viewer)
autocleaneeg-view path/to/yourfile.set

# Explicitly open the viewer (also supported for clarity)
autocleaneeg-view path/to/yourfile.vhdr --view

# Load without viewing (just validate the file)
autocleaneeg-view path/to/yourfile.fif --no-view

Note: autoclean-view remains available as a legacy alias of autocleaneeg-view for backward compatibility.

NeuroNexus support (.xdat, .nnx, .nex) is included by default and uses Neo’s NeuroNexusIO under the hood.

🧪 Test With Simulated Data

Don't have EEG data handy? Generate realistic test data to try it out:

# Generate a 10-second recording with 32 channels
python scripts/generate_test_data.py --output data/simulated_eeg.set

# Quick test all in one step
./scripts/test_with_simulated_data.sh

Simulation Options

Customize your simulated data:

python scripts/generate_test_data.py --help

• --duration 60: Create a 60-second recording
• --sfreq 512: Set sampling rate to 512 Hz
• --channels 64: Generate 64 channel EEG
• --no-events: Disable simulated event markers
• --no-artifacts: Generate clean data without eye blinks/artifacts

📋 Requirements

• Python 3.9 or higher
• MNE-Python 1.7+
• MNE-QT-Browser 0.5.2+
• PyQt5 (macOS) or compatible Qt backend

For detailed installation instructions, see INSTALL.md.

📝 License

MIT License