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Donges JF, Heitzig J, Beronov B, Wiedermann M, Runge J, Feng QY, Tupikina L, Stolbova V, Donner RV, Marwan N, Dijkstra HA, Kurths J. Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package. CHAOS (WOODBURY, N.Y.) 2015; 25:113101. [PMID: 26627561 DOI: 10.1063/1.4934554] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
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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Affiliation(s)
- Jonathan F Donges
- Potsdam Institute for Climate Impact Research, P.O. Box 601203, D-14412 Potsdam, Germany
| | - Jobst Heitzig
- Potsdam Institute for Climate Impact Research, P.O. Box 601203, D-14412 Potsdam, Germany
| | - Boyan Beronov
- Potsdam Institute for Climate Impact Research, P.O. Box 601203, D-14412 Potsdam, Germany
| | - Marc Wiedermann
- Potsdam Institute for Climate Impact Research, P.O. Box 601203, D-14412 Potsdam, Germany
| | - Jakob Runge
- Potsdam Institute for Climate Impact Research, P.O. Box 601203, D-14412 Potsdam, Germany
| | - Qing Yi Feng
- Institute for Marine and Atmospheric Research Utrecht (IMAU), Department of Physics and Astronomy, Utrecht University, Utrecht, The Netherlands
| | - Liubov Tupikina
- Potsdam Institute for Climate Impact Research, P.O. Box 601203, D-14412 Potsdam, Germany
| | - Veronika Stolbova
- Potsdam Institute for Climate Impact Research, P.O. Box 601203, D-14412 Potsdam, Germany
| | - Reik V Donner
- Potsdam Institute for Climate Impact Research, P.O. Box 601203, D-14412 Potsdam, Germany
| | - Norbert Marwan
- Potsdam Institute for Climate Impact Research, P.O. Box 601203, D-14412 Potsdam, Germany
| | - Henk A Dijkstra
- Institute for Marine and Atmospheric Research Utrecht (IMAU), Department of Physics and Astronomy, Utrecht University, Utrecht, The Netherlands
| | - Jürgen Kurths
- Potsdam Institute for Climate Impact Research, P.O. Box 601203, D-14412 Potsdam, Germany
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Correction: Local Difference Measures between Complex Networks for Dynamical System Model Evaluation. PLoS One 2015; 10:e0129413. [PMID: 26042798 PMCID: PMC4456000 DOI: 10.1371/journal.pone.0129413] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
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