Potsdam Institute for Climate Impact Research (PIK)
Interdisciplinary Center for Dynamics of Complex Systems (University of Potsdam)
Cardiovascular Physics Group (Humboldt-Universität zu Berlin)
PIK Logo
TOCSY - Toolboxes for Complex Systems
PIK/ Antique/ Blue
Home Home
ACE - Nonlinear Regression Analysis ACE
Adaptive Filtering Procedure Adaptive Filtering
CoinCalc - Event Coincidence Analysis CoinCalc
COPRA - Constructing Proxy Records From Age Models COPRA
Cross Recurrence Plot Toolbox CRP Toolbox
Commandline Recurrence Plots Commandline RPs
Analyse Coupling of Transient Dynamics Coupling Analysis
Identification of Coupling Direction Coupling Direction
Inner Composition Alignment IOTA
Dynamical Invariants by Recurrence Plots K2
Toolbox for the analysis of non-equidistantly sampled time series NEST
DSProlog DSProlog
PECUZAL PECUZAL
Permutation Entropy PETROPY
pyunicorn ‐ UNIfied COmplex Network and Recurrence aNalysis toolbox pyunicorn
Symbolic Dynamics from Recurrence Plots RECGRAM
Recurrence Plots for MATLAB RP
Recurrence Structure Analysis RSA
Wavelet and Coherence Analysis SOWAS
System Identification Tool System Identification
Time Series Graph and Momentary Information Transfer Estimation TiGraMITe

Search  Search

The following toolboxes for modelling of dynamical systems and time series analysis were developed in the Interdisciplinary Center for Dynamics of Complex Systems Potsdam, the Cardiovascular Physics Group at the Humboldt-Universität zu Berlin, and the Potsdam Institute for Climate Impact Research (PIK):

  • ACE – Nonlinear Regression Analysis
    Voss, H., Kurths, J.: Reconstruction of nonlinear time delay models from data by the use of optimal transformations, Phys. Lett. A, 234, 1997, 336-344, doi:10.1016/S0375-9601(97)00598-7.
    Voss, H., Kolodner, P., Abel, M., Kurths, J.: Amplitude equations from spatiotemporal binary-fluid convection data. Phys. Rev. Lett., 83(17), 1999, 3422-3425, doi:10.1103/PhysRevLett.83.3422.

  • Adaptive Filtering Procedure
    Wessel, N., Voss, A., Malberg, H., Ziehmann, Ch., Voss, H. U., Schirdewan, A., Meyerfeldt, U., Kurths, J.: Nonlinear analysis of complex phenomena in cardiological data, Herzschr. Elektrophys., 11(3), 2000, 159-173, doi:10.1007/s003990070035.

  • CoinCalc – Toolbox for estimation of event coincidences
    Siegmund, J. F., Siegmund, N., Donner, R. V.: CoinCalc – A new R package for quantifyung simultaneities of event series, Computers & Geosciences, 98, 2017, 64. doi:10.1016/j.cageo.2016.10.004.

  • COPRA – Constructing Proxy Records From Age Models (Ver , last mod. )
    Breitenbach, S. F. M., Rehfeld, K., Goswami, B., Baldini, J. U. L., Ridley, H. E., Kennett, D., Prufer, K., Aquino, V. V., Asmerom, Y., Polyak, V. J., Cheng, H., Kurths, J., Marwan, N.: COnstructing Proxy Records from Age models (COPRA), Climate of the Past, 8, 2012, 1765-1779 doi:10.5194/cp-8-1765-2012.

  • Commandline Recurrence Plots (Ver 1.13z, last mod. 2006-03-08)
    Marwan, N., Romano, M. C., Thiel, M., Kurths, J.: Recurrence Plots for the Analysis of Complex Systems, Physics Reports, 438(5-6), 2007, 237-329, doi:10.1016/j.physrep.2006.11.001.

  • Cross Recurrence Plot Toolbox (Ver 5.24 (R34), last mod. 09-Mar-2022 21:21:16)
    Marwan, N., Wessel, N., Meyerfeldt, U., Schirdewan, A., Kurths, J.: Recurrence Plot Based Measures of Complexity and its Application to Heart Rate Variability Data, Phys. Rev. E, 66(2), 2002, 026702, doi:10.1103/PhysRevE.66.026702.
    Marwan, N., Thiel, M., Nowaczyk, N. R.: Cross Recurrence Plot Based Synchronization of Time Series, Nonlin. Proc. Geophys., 9, 2002, 325-331, url:www.copernicus.org/EGU/npg/9/325.htm.
    Marwan, N., Kurths, J.: Nonlinear analysis of bivariate data with cross recurrence plots, Phys. Lett. A, 302(5-6), 2002, 299-307, doi:10.1016/S0375-9601(02)01170-2.
    Marwan, N., Romano, M. C., Thiel, M., Kurths, J.: Recurrence Plots for the Analysis of Complex Systems, Physics Reports, 438(5-6), 2007, 237-329, doi:10.1016/j.physrep.2006.11.001.
    Schinkel, S., Marwan, N., Dimigen, O. Kurths, J.: Confidence Bounds of recurrence-based complexity measures, Physics Letters A, 373(26), 2009, 2245-2250, doi:10.1016/j.physleta.2009.04.045.

  • Identification of Coupling Direction
    Rosenblum, M. G., Cimponeriu, L., Bezerianos, A., Patzak, A. and Mrowka, R.: Identification of coupling direction: Application to cardiorespiratory interaction, Phys. Rev. E, 65, 2002, 041909, doi:10.1103/PhysRevE.65.041909.

  • Inner Composition Alignment (IOTA)
    Hempel, S., Koseska, A., Kurths, J., Nikoloski, Z.: Inner Composition Alignment for Inferring Directed Networks from Short Time Series, Phys. Rev. Lett., 107(5), 054101, 2011, doi:10.1103/PhysRevLett.107.054101
    Hempel, S., Koseska, A., Nikoloski, Z.: Data-driven reconstruction of directed networks, Europ. Phys. J. B, 86, 250, 2013, doi:10.1140/epjb/e2013-31111-8

  • K2 - Dynamical Invariants by Recurrence Plots
    Thiel, M., Romano, M. C., J. Kurths, J.: Analytical Description of Recurrence Plots of white noise and chaotic processes, Izvestija vyssich ucebnych zavedenij/ Prikladnaja nelinejnaja dinamika - Applied Nonlinear Dynamics, 11(3), 2003, 20-30.
    Marwan, N., Romano, M. C., Thiel, M., Kurths, J.: Recurrence Plots for the Analysis of Complex Systems, Physics Reports, 438(5-6), 2007, 237-329, 10.1016/j.physrep.2006.11.001.

  • NEST ‐ Toolbox for the analysis of non-equidistantly sampled time series
    Rehfeld, K., Marwan, N., Heitzig, J., Kurths, J.: Comparison of correlation analysis techniques for irregularly sampled time series, Nonlin. Proc. Geophys., 18(3), 389-404, 2011.
    Rehfeld, K., Kurths, J.: Similarity measures for irregular and age uncertain time series, Clim. Past., 10, 107-122, 2014.

  • DS Prolog
    Hübner, S.: Wissensbasierte Modellierung von Klassifikatoren für Zeit-Frequenz-Muster in PCM-Daten, Logos Verlag, Berlin, ISBN 978-3-8325-1596-6, 2007.

  • PECUZAL for MATLAB, Julia, and Python
    Kraemer, K. H., Datseris, G., Kurths, J., Kiss, I. Z., Ocampo-Espindola, J. L., Marwan, N.: A unified and automated approach to attractor reconstruction, New J. Phys., 23(3), 033017, doi:10.1088/1367-2630/abe336.

  • Permutation Entropy
    Riedl, M., Müller, A., Wessel, N.: Practical considerations of permutation entropy, Eur. Phys. J. ST, 222(2), 249-262, 2013.

  • pyunicorn ‐ UNIfied COmplex Network and Recurrence aNalysis toolbox
    Donges, J. F., Heitzig, J., Beronov, B., Wiedermann, M., Runge, J., Feng, Q. Y., … Kurths, J.: Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package, Chaos, 25(11), 113101, 2015, doi:10.1063/1.4934554.

  • Recurrence Plots for MATLAB
    Trauth, M. H., Asrat, A., Duesing, W., Foerster, V., Kraemer, K. H., Marwan, N., Maslin, M. A., Schaebitz, F.: Classifying past climate change in the Chew Bahir basin, southern Ethiopia, using recurrence quantification analysis, Clim. Dyn., 53(5), 2557–2572, 2019, doi:10.1007/s00382-019-04641-3.

  • Recurrence Structure Analysis
    Hutt, A., beim Graben, P.: Sequences by Metastable Attractors: Interweaving Dynamical Systems and Experimental Data, Front. Appl. Math. Stat., 3, 11, 2017, doi:10.3389/fams.2017.00011.

  • Symbolic Dynamics from Recurrence Plots
    beim Graben, P., Hutt, A.: Detecting recurrence domains of dynamical systems by symbolic dynamics, Phys. Rev. Lett., 110, 154101, 2013, doi:10.1103/PhysRevLett.110.154101.

  • System Identification Tool (Ver 1.6.1 (R9.3b), last mod. 25-Feb-2008 12:34:15)
    Sitz, A., Schwarz, U., Kurths, J., Voss, H. U.: Estimation of parameters and unobserved components for nonlinear systems from noisy time series, Phys. Rev. E, 66, 2002, 016210, doi:10.1103/PhysRevE.66.016210.

  • TIGRAMITE ‐ Time Series Graph and Momentary Information Transfer Estimation
    Runge, J., Heitzig, J., Marwan, N., Kurths, J.: Quantifying Causal Coupling Strength: A Lag-specific Measure For Multivariate Time Series Related To Transfer Entropy, Physical Review E, 86, 2012, 061121.
    Runge, J., Heitzig, J., Petoukhov, V., Kurths, J.: Escaping the Curse of Dimensionality in Estimating Multivariate Transfer Entropy, Physical Review Letters, 108, 2012, 258701.

  • SOWAS – Wavelet Spectral and Coherence Analysis
    Maraun, D., Kurths, J.: Cross Wavelet Analysis. Significance Testing and Pitfalls, Nonlin. Proc. Geoph., 11, 2004, 505-514, doi:10.5194/npg-11-505-2004.


Applicability: Illustrative examples  Illustrative examples of TOCSY


If you use data, software or other stuff from this web site, please cite the corresponding publication and this web site (tocsy.pik-potsdam.de)!
         


Information and contact:
Norbert Marwan
tocsy

The authors of the programmes are responsible for their submissions.

last modified: 2022-03-29, 09:24:19


© 2004-2022 SOME RIGHTS RESERVED
University of Potsdam, Interdisciplinary Center for Dynamics of Complex Systems, Germany
Potsdam Institute for Climate Impact Research, Complexity Science, Germany

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 2.0 Germany License.
Imprint, Data policy, Disclaimer, Accessibility statement

Please respect the copyrights! The content is protected by the Creative Commons License. If you use the provided programmes, text or figures, you have to refer to the given publications and this web site (tocsy.pik-potsdam.de) as well.

@MEMBER OF PROJECT HONEY POT
Spam Harvester Protection Network
provided by Unspam