pyunicorn (Unified Complex Network and RecurreNce
analysis toolbox) is a fully object-oriented Python package for the advanced
analysis and modeling of complex networks. Above the standard measures of
complex network theory such as degree, betweenness and clustering coefficient
it provides some uncommon but interesting statistics like Newman's random
pyunicorn features novel node-weighted (node splitting
invariant) network statistics as well as measures designed for analyzing
networks of interacting/interdependent networks.
pyunicorn allows to easily construct networks from uni- and
multivariate time series data (functional (climate) networks and recurrence
networks). This involves linear and nonlinear measures of time series analysis
for constructing functional networks from multivariate data as well as modern
techniques of nonlinear analysis of single time series like recurrence
quantification analysis (RQA) and recurrence network analysis.
On a local development version, HTML and PDF documentation can be generated
$> pip install --user -e . $> cd docs; make clean html latexpdf
pyunicorn relies on the following open source or freely available packages
which have to be installed on your machine.
- Optional (used only in certain classes and methods):
- 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
For development, especially if you want to test
pyunicornfrom within the source directory:
$> pip install -r requirements.txt --user -e .
Before committing changes to the code base, please make sure that all tests pass. The test suite is managed by tox and configured to use system-wide packages when available. Thus to avoid frequent waiting, we recommend you to install the current versions of the following packages:
$> pip install networkx matplotlib basemap Sphinx $> pip install tox pylint pytest pytest-xdist pytest-flake8
The test suite can be run from anywhere in the project tree by issuing:
To expose the defined test environments and target them independently:
$> tox -l $> tox -e units,style
To test individual files:
$> py.test tests/test_core/TestNetwork.py # unit tests $> py.test --doctest-modules pyunicorn/core/network.py # doctests $> py.test --flake8 pyunicorn/core/network.py # style $> pylint pyunicorn/core/network.py # code analysis
Not implemented yet.
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].
pyunicorn is BSD-licensed (3 clause).