neuralib-imaging 0.7.2

Tools for cellular imaging and widefield imaging

neuralib-imaging

Tools for cellular imaging and widefield imaging analysis, providing spike inference, image registration, and widefield data processing for neuroscience research.

Overview

neuralib-imaging provides Python tools for analyzing calcium imaging and widefield imaging data. It includes:

• Spike Inference: CASCADE (deep learning), OASIS deconvolution
• Registration: Coordinate transformation and atlas alignment
• Widefield Analysis: FFT processing, SVD decomposition, hemodynamic correction
• Visualization: Interactive napari-based viewers and plotting tools

Installation

From PyPI

pip install neuralib-imaging

With Optional Dependencies

# CASCADE spike inference (requires TensorFlow)
pip install neuralib-imaging[cascade]

# Widefield analysis (requires napari, bokeh, scikit-learn)
pip install neuralib-imaging[widefield]

# All features
pip install neuralib-imaging[all]

From Source (uv recommended)

git clone https://github.com/ytsimon2004/neuralib2.git
cd neuralib2/packages/neuralib-imaging
uv pip install -e .        # Basic installation
uv pip install -e ".[all]" # With optional features

Requirements

• Python 3.11 or 3.12
• Core dependencies: neuralib-utils, numpy, numba, matplotlib
• See pyproject.toml for optional dependencies

Documentation

• Main Documentation: https://neuralib2.readthedocs.io/
• GitHub Repository: https://github.com/ytsimon2004/neuralib2
• Issue Tracker: https://github.com/ytsimon2004/neuralib2/issues

License

BSD 3-Clause License. See LICENSE file for details.

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Submit a pull request with clear description

For bug reports and feature requests, use the GitHub issue tracker.

Acknowledgments

This package integrates with:

• CASCADE - Deep learning spike inference
• napari - Multi-dimensional image viewer