Download

Documentation

For extensive HTML documentation, jump right to the pyunicorn homepage. Recent PDF versions are also available.

On a local development version, HTML and PDF documentation can be generated using Sphinx:

$> pip install --user -e .
$> cd docs; make clean html latexpdf

Dependencies

pyunicorn is written in Python 3.7. The software is quite flexible, we have it running on Linux and MacOSX machines, the institute’s IBM iDataPlex cluster and even on Windows. It relies on the following open source or freely available packages which have to be installed on your machine.

Required:
Optional (used only in certain classes and methods):

Numpy, Scipy, Matplotlib, igraph and other packages should be available via a package management system on Linux or MacOSX. All packages can be downloaded, compiled and installed following the instructions on their homepages.

An easy way to go may be a Python distribution like Anaconda that already includes many libraries.

Installation

Stable release

Via the Python Package Index:

$> pip install pyunicorn
Development version

For a simple system-wide installation:

$> pip install -r requirements.txt .

Depending on your system, you may need root privileges. On UNIX-based operating systems (Linux, Mac OS X etc.) this is achieved with sudo.

For development, especially if you want to test pyunicorn from within the source directory:

$> pip install -r requirements.txt --user -e .

Reference

Please acknowledge and cite the use of this software and its authors when results are used in publications or published elsewhere. You can use the following reference:

J.F. Donges, J. Heitzig, B. Beronov, M. Wiedermann, J. Runge, Q.-Y. Feng, L. Tupikina, V. Stolbova, R.V. Donner, N. Marwan, H.A. Dijkstra, and J. Kurths, Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package, Chaos 25, 113101 (2015), doi:10.1063/1.4934554, Preprint: arxiv.org:1507.01571 [physics.data-an].

Funding

The development of pyunicorn has been supported by various funding sources, notably the German Federal Ministry for Education and Research (projects GOTHAM and CoSy-CC2), the Leibniz Association (projects ECONS and DominoES), the German National Academic Foundation, and the Stordalen Foundation via the Planetary Boundary Research Network (PB.net) among others.