PyPhi is a Python library for computing integrated information.
If you use this software in your research, please cite the paper:
Mayner WGP, Marshall W, Albantakis L, Findlay G, Marchman R, Tononi G. (2018)PyPhi: A toolbox for integrated information theory.PLOS Computational Biology 14(7): e1006343.
An illustrated tutorial on how Φ is calculated is available as a supplement to the paper.
To report issues, use the issue tracker on the GitHub repository. Bug reports and pull requests are welcome.
For general discussion, you are welcome to join the pyphi-users group.
To install the latest stable release, run
pip install pyphi
To install the latest development version, which is a work in progress and may have bugs, run
pip install "git+https://github.com/wmayner/pyphi@develop#egg=pyphi"
For detailed instructions on how to install PyPhi on macOS, see the Detailed installation guide for macOS.
Windows users: PyPhi is only supported on Linux and macOS operating
systems. However, you can run it on Windows by using the Anaconda Python distribution and installing
PyPhi with conda:
conda install -c
- Loading a configuration
- Approximations and theoretical options
- Parallelization and system resources
- Memoization and caching
- Numerical precision