We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology.
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November 2015
Research Article|
November 04 2015
Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package
Jonathan F. Donges;
Jonathan F. Donges
a)
1
Potsdam Institute for Climate Impact Research
, P.O. Box 601203, D-14412 Potsdam, Germany
2Stockholm Resilience Centre,
Stockholm University
, Kräftriket 2B, 114 19 Stockholm, Sweden
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Jobst Heitzig;
Jobst Heitzig
1
Potsdam Institute for Climate Impact Research
, P.O. Box 601203, D-14412 Potsdam, Germany
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Boyan Beronov
;
Boyan Beronov
1
Potsdam Institute for Climate Impact Research
, P.O. Box 601203, D-14412 Potsdam, Germany
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Marc Wiedermann;
Marc Wiedermann
1
Potsdam Institute for Climate Impact Research
, P.O. Box 601203, D-14412 Potsdam, Germany
3Department of Physics,
Humboldt University Berlin
, Newtonstr. 15, D-12489 Berlin, Germany
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Jakob Runge;
Jakob Runge
1
Potsdam Institute for Climate Impact Research
, P.O. Box 601203, D-14412 Potsdam, Germany
3Department of Physics,
Humboldt University Berlin
, Newtonstr. 15, D-12489 Berlin, Germany
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Qing Yi Feng;
Qing Yi Feng
4Institute for Marine and Atmospheric Research Utrecht (IMAU), Department of Physics and Astronomy,
Utrecht University
, Utrecht, The Netherlands
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Liubov Tupikina;
Liubov Tupikina
1
Potsdam Institute for Climate Impact Research
, P.O. Box 601203, D-14412 Potsdam, Germany
3Department of Physics,
Humboldt University Berlin
, Newtonstr. 15, D-12489 Berlin, Germany
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Veronika Stolbova;
Veronika Stolbova
1
Potsdam Institute for Climate Impact Research
, P.O. Box 601203, D-14412 Potsdam, Germany
3Department of Physics,
Humboldt University Berlin
, Newtonstr. 15, D-12489 Berlin, Germany
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Reik V. Donner;
Reik V. Donner
1
Potsdam Institute for Climate Impact Research
, P.O. Box 601203, D-14412 Potsdam, Germany
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Norbert Marwan
;
Norbert Marwan
1
Potsdam Institute for Climate Impact Research
, P.O. Box 601203, D-14412 Potsdam, Germany
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Henk A. Dijkstra;
Henk A. Dijkstra
4Institute for Marine and Atmospheric Research Utrecht (IMAU), Department of Physics and Astronomy,
Utrecht University
, Utrecht, The Netherlands
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Jürgen Kurths
Jürgen Kurths
1
Potsdam Institute for Climate Impact Research
, P.O. Box 601203, D-14412 Potsdam, Germany
3Department of Physics,
Humboldt University Berlin
, Newtonstr. 15, D-12489 Berlin, Germany
5Institute for Complex Systems and Mathematical Biology,
University of Aberdeen
, Aberdeen AB24 3FX, United Kingdom
6Department of Control Theory,
Nizhny Novgorod State University
, Gagarin Avenue 23, 606950 Nizhny Novgorod, Russia
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a)
Electronic mail: [email protected]
Chaos 25, 113101 (2015)
Article history
Received:
July 01 2015
Accepted:
October 12 2015
Citation
Jonathan F. Donges, Jobst Heitzig, Boyan Beronov, Marc Wiedermann, Jakob Runge, Qing Yi Feng, Liubov Tupikina, Veronika Stolbova, Reik V. Donner, Norbert Marwan, Henk A. Dijkstra, Jürgen Kurths; Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package. Chaos 1 November 2015; 25 (11): 113101. https://doi.org/10.1063/1.4934554
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