meeg-utils 0.1.2

A Python-based MEEG processing toolkit primarily based on MNE-Python.

meeg-utils

A Python-based MEG/EEG processing toolkit built on MNE-Python, providing a high-level, user-friendly API for processing MEG/EEG data.

Features

Preprocessing

Epoching In Progress

• High-level PreprocessingPipeline class for streamlined MEG/EEG preprocessing.

Feature Extraction

In Progress

• Common MEG/EEG features (e.g., power spectral density, connectivity metrics).

📦 Installation

pip install meeg-utils

🚀 Quick Start

from meeg_utils.preprocessing import PreprocessingPipeline
from mne_bids import BIDSPath

# Create pipeline
pipeline = PreprocessingPipeline(
    input_path=BIDSPath(
        subject="01", session="01", task="rest",
        datatype="eeg", root="/data/bids"
    ),
    output_dir="/data/output"
)

# Run preprocessing
result = pipeline.run(
    filter_params={"highpass": 0.1, "lowpass": 100.0, "sfreq": 250.0},
    detect_bad_channels=True,
    remove_line_noise=True,
    apply_ica=True
)

# Save results
pipeline.save()

Batch processing:

from meeg_utils.preprocessing import BatchPreprocessingPipeline

# Process multiple subjects in parallel
batch = BatchPreprocessingPipeline(
    input_paths=bids_paths,  # List of BIDSPaths
    output_dir="/data/output",
    n_jobs=4  # Use 4 parallel workers
)

batch.run(detect_bad_channels=True, remove_line_noise=True, apply_ica=True)

📚 Documentation

Full documentation: https://colehank.github.io/meeg-utils/

• Installation Guide
• Quick Start
• Preprocessing Guide
• Batch Processing
• API Reference
• Contributing Guide

🛠️ Development

# Clone and setup
git clone https://github.com/colehank/meeg-utils.git
cd meeg-utils
uv sync --dev
uv run pre-commit install

# Run tests
uv run pytest

# Build docs
cd docs && uv run make html

See the Contributing Guide for detailed development instructions.

📄 License

MIT License - see LICENSE file for details.

🙏 Acknowledgments

Built on the excellent MNE-Python ecosystem.

📞 Support

• 📖 Documentation
• 🐛 Issue Tracker
• 💬 Discussions