opticalmapping 0.2.0

A toolbox for analyzing optical mapping and fluorescence imaging data.

optimap

optimap: An open-source library for the processing of fluorescence video 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 loading, processing and exporting videos, extracting and measuring optical traces, visualizing action potential or calcium waves, tracking motion and compensating motion artifacts, computing activation maps, measuring contractility and further analyzing and visualizing the results. Refer to the Tutorials and the Documentation for more detailed information about optimap's usage and features.

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

Installation

optimap is available for Mac OSX, Windows and Linux, see Installing optimap for more detailed information.

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

Pre-built binaries can be installed using pip:

pip install opticalmapping[all]

The above command 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

Getting Started

See Tutorials and the Getting Started guide for an introduction to optimap and installation instructions.

About optimap

optimap is a script-based software, which means that you run Python-based analysis scripts rather than using a graphical user interface. We provide several example scripts which explain the usage of optimap, see Tutorials. The example scripts can also be downloaded directly by clicking on the right link in the green box at the top of each tutorial page. optimap is developed by members of the Cardiac Vision Laboratory at the University of California, San Franicsco. optimap was created for cardiovascular scientists in particular, but might also be useful for scientists in other fields, for instance, when performing calcium imaging or physiological research with moving cells or tissues. optimap is open-source, freely available, and relies on open-source packages such as NumPy, SciPy, matplotlib and OpenCV.

Links

• Documentation
• Issue tracker
• Source code

Contributing

We welcome bug reports, questions, ideas for new features and pull-requests to fix issues or add new features to optimap. See Contributing for more information.

License

optimap is licensed under the MIT License.