A simple interface to cardiac cellular electrophysiology
Myokit is an open-source Python-based toolkit that facilitates modeling and simulation of cardiac cellular electrophysiology. It's hosted on GitHub and available on PyPi. For the latest documentation, see myokit.readthedocs.io.
For full installation details (on linux, mac, or windows), please see http://myokit.org/install. A shorter installation guide for experienced users is given below.
To install Myokit, using PyQt5 for Myokit's GUI components, run:
pip install myokit[pyqt]
to use PySide2 instead, run:
pip install myokit[pyside]
If you're not planning to use the GUI components (for example to run simulations on a server), you can simply install with
pip install myokit
On Linux and Windows, start menu icons can be added by running
python -m myokit icons
To run single-cell simulations, CVODES must be installed (but Windows users can skip this step, as binaries are included in the pip install). In addition, Myokit needs a working C/C++ compiler to be present on the system.
Existing Myokit installations can be upgraded using
pip install --upgrade myokit
After installation, to quickly test if Myokit works, type
python -m myokit run example
myokit run example
To open an IDE window, type
To see what else Myokit can do, type
Contributing to Myokit
You can contribute to Myokit by reporting issues, but code contributions (bugfixes, new formats, new features etc.) are also very welcome! New features are best discussed in an issue before starting any implementation work, and guidelines for code style (and more) can be found in CONTRIBUTING.md.
If you use Myokit in your research, please cite it using the information in our CITATION file.
I like to keep track of who's using Myokit (for my CV!). If you are using Myokit for teaching, I'd love to hear about it. You can drop me a line at michael[at]myokit.org.
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