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.
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
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