pysoplot 0.0.2

Description:

pysoplot 0.0.2

Pysoplot
Pysoplot is a Python library that provides basic functions and routines for geochronology. It implements some of the core functionality of the popular (and now defunct) Isoplot/Ex. software, but also includes new algorithms and routines. Pysoplot is intended to be used by geochronologists to build custom scripts and data processing routines in order to meet individual requirements.
Pysoplot includes functions for:


regressing 2-D data using the model 1, 2 and 3 algorithms popularised by Isoplot/Ex.


regressing 2-D data using the robust spine algorithm of Powell et al. (2020) and a new "robust model 2" algorithm


computing weighted averages using algorithms based on classical and robust statistics


computing classical isochron and U-Pb concordia-intercept ages


plotting isochron diagrams


computing disequilibrium U-Pb ages


plotting equilibrium and disequilibriam concordia curves, age ellipses, and uncertainty envelopes


computing age uncertainties using Monte Carlo methods


Full code documentation is coming soon.
Installation
Run the following to install:
pip install pysoplot

Example usage
import pysoplot as pp

# get Tera-Wasserburg test dataset
dp = pp.data.LA0708
# transform data point errors from 2 sigma to 1 sigma absolute
dp = pp.transform.dp_errors(dp, 'abs2s')

# regress data
fit = pp.regression.robust_fit(*dp, plot=True, diagram='tw')
pp.misc.print_result(fit, 'Regression results')
fit['fig'].show()

# compute Tera-Wasserburg concordia-intercept age
result = pp.upb.concint_age(fit, method='Powell')
print(f"age: {result['age']:.2f} +/- {result['age_95pm']:.2f}")

Acknowledgements
Acknowledgement of all third-party algorithms implemented in Pysoplot with links to publications will be added here soon...
License
Pysoplot is distributed under the MIT license.
Contact
Timothy Pollard