This project contains files with functions written in python related to directional predictions, simulation of synthetic samples and directional analyses with correction of within-sites error. It is based on the simplified zonal giant Gaussian process models presented by Brandt et al. (2020, GJI, DOI: ggaa258).
The synthetic simulations need the previous installation of the PMAGPY package.
The files that contains the main functions are:
Contains theoretical determinations for variances and covariances for a given zonal GGP model, the pdf map of the GGP model s(u) in equal-area coordinates, mean values, standard deviations.
A jupyter notebook **"Theoretical_predictions_directional_analises_GGPmodels_Brandtetal2019.ipynb"** was created to help the user know more about these functions.
Contains determinations of mean, standard deviations, elongation and variability for a set of directional directions rotated to the vertical in equal-area coordinates.
Contains functions for simulating synthetic directions and calculating the PSV directional measurements.
This file needs the previous instalation of PMAGPY package (https://github.com/PmagPy/PmagPy).
A jupyter notebook **"Simulation of synthetic directions from zonal GGP models and experimental results.ipynb"** was created to help the user know more about these functions.