Package Reference Documentation¶
The following classes and methods form the isotopylog package:
isotopylog classes¶
isotopylog.EDistribution (kds, **kwargs) |
Class for inputting, storing, and visualizing clumped isotope activation energies. |
isotopylog.HeatingExperiment (dex, T, tex, …) |
Class for inputting, storing, and visualizing clumped isotope heating experiment data. |
isotopylog.kDistribution (params, model, T, …) |
Class for inputting, storing, and visualizing clumped isotope rate data. |
isotopylog methods¶
isotopylog.calc_L_curve (he[, ax, kink, …]) |
Function to choose the “best” omega value for regularization following the Tikhonov Regularization method. |
isotopylog.derivatize (num, denom) |
Method for derivatizing numerator, num, with respect to denominator, denom. |
isotopylog.fit_Arrhenius (T, lnk[, lnk_std, …]) |
Determines the activation energy by fitting an Arrhenius plot. |
isotopylog.fit_Hea14 (he[, logy, p0]) |
Fits D evolution data using the transient defect/equilibrium model of Henkes et al. |
isotopylog.fit_HH21 (he[, nu_max, nu_min, …]) |
Fits D evolution data using the distributed activation energy model of Hemingway and Henkes (2021). |
isotopylog.fit_HH21inv (he[, nu_max, nu_min, …]) |
Fits D evolution data using the distributed activation energy model of Hemingway and Henkes (2021). |
isotopylog.fit_PH12 (he[, logy, p0, thresh]) |
Fits D evolution data using the first-order model approximation of Passey and Henkes (2012). |
isotopylog.fit_SE15 (he[, p0, mp, z]) |
Fits D evolution data using the paired diffusion model of Stolper and Eiler (2015). |
isotopylog.geologic_history (t, T, ed, d0[, …]) |
Predicts the D47 evolution when a given ipl.EDistribution model is subjected to any arbitrary time-temperature history. |
References¶
The following references were used during creation of the core isotopylog
pacakge or provide information regarding the choice of user-inputted parameters.
- Craig (1957) Geochim. Cosmochim. Ac., 12, 133–149.
- Li et al. (1988) Chin. Sci. Bull., 33, 1610–1613.
- Chang and Li (1990) Chin. Sci. Bull., 35, 290.
- Hansen (1994) Numerical Algorithms, 6, 1-35.
- Gonfiantini (1995) IAEA Technical Report, 825.
- Assonov and Brenninkmeijer (2003) Rapid Comm. Mass Spec., 17, 1017–1029.
- Barkan and Luz (2005) Rapid Comm. Mass Spec., 19, 3737–3742.
- Ghosh et al. (2006) Geochim. Cosmochim. Ac., 70, 1439–1456.
- Brand (2010) Pure Appl. Chem., 82, 1719–1733.
- Dennis et al. (2011) Geochim. Cosmochim. Ac., 75, 7117–7131.
- Forney and Rothman (2012) J. Royal Soc. Inter., 9, 2255–2267.
- Passey and Henkes (2012) Earth Planet. Sci. Lett., 351, 223–236.
- Passey et al. (2014) Geochim. Cosmochim. Ac., 141, 1–25.
- Henkes et al. (2014) Geochim. Cosmochim. Ac., 139, 362–382.
- Stolper and Eiler (2015) Am. J. Sci., 315, 363–411.
- Daëron et al. (2016) Chem. Geol., 442, 83–96.
- Bonifacie et al. (2017) Geochim. Cosmochim. Ac., 200, 255–279.
- Brenner et al. (2018) Geochim. Cosmochim. Ac., 224, 42–63.
- Lloyd et al. (2018) Geochim. Cosmochim. Ac., 242, 1–20.
- Chen et al. (2019) Geochim. Cosmochim. Ac., 258, 156–173.
- Anderson et al. (2021) Geophys. Res. Lett., 48, e2020GL092069.
- Bernasconi et al. (2021) Geochem., Geophys., Geosys., 22, e2020GC009588.
- Hemingway and Henkes (2021) Earth Planet. Sci. Lett., 566, 116962.
- Looser et al. (2023) Geochim. Cosmochim. Ac., 350, 1–15.