Project · Citation

Citation¶

If TSDynamics contributes to published work, please cite it — and, just as importantly, cite the original papers behind the methods and models you relied on. The scholarly credit belongs first to the people who invented the model and the algorithm; the software is the instrument.

Citing the software¶

TSDynamics is archived on Zenodo and has a persistent DOI: 10.5281/zenodo.20945679. This is the concept DOI — it always resolves to the newest release, so you never have to update it. Cite it alongside the exact version you actually used; the installed version is always available at runtime:

import tsdynamics as ts
ts.__version__          # e.g. '5.3.1'

A BibTeX entry for the software:

@software{estevez_tsdynamics,
  author  = {Estevez, Daniel},
  title   = {{TSDynamics}: compiled dynamical systems and chaos analysis for {Python}},
  year    = {2026},
  version = {5.3.1},
  doi     = {10.5281/zenodo.20945679},
  url     = {https://doi.org/10.5281/zenodo.20945679},
  note    = {MIT license. Set version = to your installed tsdynamics.__version__.}
}

Cite this repository

10.5281/zenodo.20945679 is the concept DOI: it always resolves to the newest published release. Zenodo also mints a distinct version DOI for each release, so if you need to pin a specific archived version cite that release's own DOI instead — but for a citation that never goes stale, use the concept DOI above and pin the version field to your installed tsdynamics.__version__.

Citing the methods¶

TSDynamics implements published algorithms. Alongside the software entry, cite the original paper for each method your results depend on:

You used	Cite
`lyapunov_spectrum` (QR / tangent dynamics)	Benettin, Galgani, Giorgilli & Strelcyn, Lyapunov characteristic exponents for smooth dynamical systems…, Meccanica 15, 9–30 (1980)
`max_lyapunov` (two-trajectory rescaling)	Benettin, Galgani & Strelcyn, Kolmogorov entropy and numerical experiments, Phys. Rev. A 14, 2338 (1976)
`lyapunov_from_data` (Kantz)	Kantz, A robust method to estimate the maximal Lyapunov exponent of a time series, Phys. Lett. A 185, 77 (1994)
`lyapunov_from_data` (Rosenstein)	Rosenstein, Collins & De Luca, A practical method for calculating largest Lyapunov exponents from small data sets, Physica D 65, 117 (1993)
`kaplan_yorke_dimension`	Kaplan & Yorke, Chaotic behavior of multidimensional difference equations, LNM 730, Springer (1979)
`correlation_dimension` / `correlation_sum`	Grassberger & Procaccia, Characterization of strange attractors, Phys. Rev. Lett. 50, 346 (1983)
`gali` (chaos indicator)	Skokos, Bountis & Antonopoulos, Geometrical properties of local dynamics…, Physica D 231, 30 (2007)
`zero_one_test`	Gottwald & Melbourne, A new test for chaos in deterministic systems, Proc. R. Soc. A 460, 603 (2004)
`expansion_entropy`	Hunt & Ott, Defining chaos, Chaos 25, 097618 (2015)
`permutation_entropy`	Bandt & Pompe, Permutation entropy: a natural complexity measure…, Phys. Rev. Lett. 88, 174102 (2002)
`sample_entropy`	Richman & Moorman, Physiological time-series analysis using approximate and sample entropy, Am. J. Physiol. 278, H2039 (2000)
`recurrence_matrix` / `rqa`	Marwan, Romano, Thiel & Kurths, Recurrence plots for the analysis of complex systems, Phys. Rep. 438, 237 (2007)
`embed` (delay reconstruction)	Takens, Detecting strange attractors in turbulence, LNM 898, Springer (1981)
`embedding_dimension` (Cao / FNN)	Cao, Practical method for determining the minimum embedding dimension…, Physica D 110, 43 (1997)
`surrogates` (IAAFT)	Schreiber & Schmitz, Improved surrogate data for nonlinearity tests, Phys. Rev. Lett. 77, 635 (1996)
`find_attractors` / `basins_of_attraction`	Datseris & Wagemakers, Effortless estimation of basins of attraction, Chaos 32, 023104 (2022)
`basin_entropy`	Daza, Wagemakers, Georgeot, Guéry-Odelin & Sanjuán, Basin entropy: a new tool to analyze uncertainty in dynamical systems, Sci. Rep. 6, 31416 (2016)

Each analysis page under Analysis lists the exact reference for the routines it documents, and every routine's docstring cites the paper it implements.

Citing the systems¶

Each built-in system declares its literature source in its reference class attribute — shown on its page under Systems and available programmatically from the registry:

from tsdynamics import registry

registry.get("Lorenz").reference
# 'Lorenz (1963), J. Atmos. Sci. 20, 130-141'

Most systems also carry a bare doi on the class for the primary reference, sourced where available from the published catalogue metadata:

import tsdynamics as ts

ts.systems.Lorenz.doi
# '10.1175/1520-0469(1963)020<0130:dnf>2.0.co;2'

Of the 171 built-in systems, 166 declare a literature reference and 149 carry a doi. To pull the reference for every system you touched — the makings of a \bibliography — sweep the registry:

from tsdynamics import registry

for entry in registry.all_systems():
    ref = entry.reference or "(no reference on file)"
    print(f"{entry.name:24s} {ref}")

If your results hinge on a particular model, cite its original paper. The model deserves the credit before the implementation does — the Lorenz attractor is Lorenz's, not ours.