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A toolbox for analyzing optical mapping and fluorescence imaging data.

Project description

optimap

Python toolbox for analyzing optical mapping data

optimap is an open-source Python toolbox for exploring, visualizing, and analyzing high-speed fluorescence imaging data with a focus on cardiac optical mapping data. It includes modules for data input/output, processing scientific video recordings, visualization, motion compensation, trace extraction, and analysis.

⚠️ optimap is currently in early development, expect breaking changes and bugs.

Installation

Installing pre-built binaries (Mac OSX, Windows, Linux)

pip install opticalmapping[all]

will install optimap and all recommended dependencies (including OpenCV and PySide2). If you wish to install your own version of OpenCV (e.g. for CUDA support) or Qt implementation use

pip install opticalmapping

instead. See Installing Optimap for more information.

Getting Started

See the Getting Started guide for installation instructions and a quick introduction to optimap. See the Tutorials for more detailed examples.

Links

License

optimap is licensed under the MIT License.

Project details


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