Neuroscience Training Program, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Psychiatry Department, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
PLoS Comput Biol. 2018 Jul 26;14(7):e1006343. doi: 10.1371/journal.pcbi.1006343. eCollection 2018 Jul.
Integrated information theory provides a mathematical framework to fully characterize the cause-effect structure of a physical system. Here, we introduce PyPhi, a Python software package that implements this framework for causal analysis and unfolds the full cause-effect structure of discrete dynamical systems of binary elements. The software allows users to easily study these structures, serves as an up-to-date reference implementation of the formalisms of integrated information theory, and has been applied in research on complexity, emergence, and certain biological questions. We first provide an overview of the main algorithm and demonstrate PyPhi's functionality in the course of analyzing an example system, and then describe details of the algorithm's design and implementation. PyPhi can be installed with Python's package manager via the command 'pip install pyphi' on Linux and macOS systems equipped with Python 3.4 or higher. PyPhi is open-source and licensed under the GPLv3; the source code is hosted on GitHub at https://github.com/wmayner/pyphi. Comprehensive and continually-updated documentation is available at https://pyphi.readthedocs.io. The pyphi-users mailing list can be joined at https://groups.google.com/forum/#!forum/pyphi-users. A web-based graphical interface to the software is available at http://integratedinformationtheory.org/calculate.html.
综合信息理论为全面刻画物理系统的因果结构提供了一个数学框架。在这里，我们介绍 PyPhi，这是一个 Python 软件包，它实现了这个因果分析框架，并揭示了二元离散动力系统的完整因果结构。该软件使用户能够轻松地研究这些结构，是综合信息理论形式主义的最新参考实现，并已应用于复杂性、涌现和某些生物学问题的研究。我们首先概述了主要算法，并在分析一个示例系统的过程中展示了 PyPhi 的功能，然后描述了算法设计和实现的细节。在配备了 Python 3.4 或更高版本的 Linux 和 macOS 系统上，可以通过命令“pip install pyphi”使用 Python 的包管理器安装 PyPhi。PyPhi 是开源的，并根据 GPLv3 获得许可；源代码托管在 GitHub 上，网址为 https://github.com/wmayner/pyphi。全面且不断更新的文档可在 https://pyphi.readthedocs.io 上获得。可以在 https://groups.google.com/forum/#!forum/pyphi-users 上加入 pyphi-users 邮件列表。该软件的基于网络的图形界面可在 http://integratedinformationtheory.org/calculate.html 上访问。
