isotopylog 0.0.9

Package Information

Authors:

Jordon D. Hemingway (jordon.hemingway@erdw.ethz.ch)

Version:

0.0.9

Release:

18 July 2026

License:

GNU GPL v3 (or greater)

url:

http://github.com/FluvialSeds/isotopylog http://pypi.python.org/pypi/isotopylog

doi:

How to Cite

When analyzing data with isotopylog to be used in a peer-reviewed journal, please cite this package as:

• J.D. Hemingway. isotopylog: open-source tools for clumped isotope kinetic data analysis, 2020-, http://pypi.python.org/pypi/isotopylog [online; accessed 2026-07-18]

Additionally, please cite the following peer-reviewed manuscript describing the deveopment of the package and clumped isotope data treatment:

• J.D. Hemingway and G.A. Henkes (2021) A disordered kinetic model for clumped isotope bond reordering in carbonates. Earth and Planetary Science Letters, 566, 116962.

If analyzing data with any of the previously published models, please also cite the relevant manuscript(s):

• For the pseudo-first-order model: B.H. Passey and G.A. Henkes (2012) Carbonate clumped isotope bond reordering and geospeedometry. Earth and Planetary Science Letters, 351, 223–236.

• For the transient defect/equilibrium defect model: G.A. Henkes et al. (2014) Temperature limits for preservation of primary calcite clumped isotope paleotemperatures. Geochimica et Cosmochimica Acta, 139, 362–382.

• For the pair-diffusion model: D.A. Stolper and J.M. Eiler (2015) The kinetics of solid-state isotope exchange reactions for clumped isotopes: A study of inorganic calcites and apatites from natural and experimental samples. American Journal of Science, 315, 363–411.

Documentation

The documentation for the latest release—including detailed package references and comprehensive examples detailing various steps of the data analysis process—is available at:

http://isotopylog.readthedocs.io

Package features

isotopylog currently contains the following features relevant for clumped isotope data analysis:

• Stores, culls, and plots experimental kinetic isotope data

  • Easily converts between multiple reference frames (e.g., Ghosh, CDES90, I-CDES)

  • Plots forward-modeled predictions using rate parameters (i.e., k values) in order to visually assess goodness of fit

• Estimates the rate parameters (i.e., k values) of bond reordering kinetics for a given set of experimental results using any of the following models:

  • Pseudo-first-order model (Passey and Henkes, 2012)

  • Transient defect/equilibrium defect model (Henkes et al., 2014)

  • Paired-diffusion model (Stolper and Eiler, 2015)

  • Disordered kinetic model (Hemingway and Henkes, 2021)

    • Calculates best-fit regularized (“smoothed”) rate distributions using Tikhonov Regularization

      • Automated or user-defined regularization value

      • Can include negative solutions (e.g., for fitting aragonite data with transient ∆₄₇increases)

    • Determines best-fit lognormal rate distributions

• Determines activation energy values using an Arrhenius fit to rate parameters

  • Generates Arrhenius plots (not possible for negative solutions)

  • Allows quick and easy importing of literature data

• Calculates and stores model performance metrics and goodness of fit statistics

• Ability to update published model kinetics, either by manually entering kinetic results or by fitting new experimental data

• Predicts clumped isotope evolution for a given geologic time/temperature history:

  • Allows users to assess if their results reflect primary signatures or diagenetic overprinting.

• Includes propagated uncertainty estimates for all heating experiment model fits, Arrhenius activation energy fits, and geologic history forward-model predictions.

  • Includes analytical uncertainty weighting factors when calculating heating experiment rate values.

  • Accounts for model parameter covariance using a numerical Jacobian approach.