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duserzym committed Sep 17, 2022
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# Bayesian PEP inversion

This repository contains code and results associated with a Bayesian framework for paleomagnetic Euler pole inversion and apparent polar wander path analyses. An associated manuscript can be found in this repository: https://github.com/Swanson-Hysell-Group/Bayesian_PEP_inversion_manuscript
This repository contains code and results associated with a Bayesian framework for paleomagnetic Euler pole inversion and apparent polar wander path analyses. The associated paper in JGR-Solid Earth is:

**Bayesian paleomagnetic Euler pole inversion for paleogeographic reconstruction and analysis**

Ian R. Rose<sup>1</sup>, Yiming Zhang<sup>1</sup>, and Nicholas L. Swanson-Hysell<sup>1</sup>

### bayesian_pep

This folder contains the Python library.

<sup>1</sup>Department of Earth and Planetary Science, University of California, Berkeley, CA, USA

The manuscript files be found in this repository: https://github.com/Swanson-Hysell-Group/Bayesian_PEP_inversion_manuscript

#### data
## Repository structure

This folder contains compiled data used for generating examples of apparent polar wander path inversions.
### bayesian_pep

This folder contains the Python library.

### code_output

#### Jupyter Notebooks
This folder contains visualizations as well as raw PyMC output from the Jupyter notebooks .

Notebooks are used to demonstrate the functions of the package, to conduct analysis, and to develop visualizations that are presented in the accompanying manuscript.
### data

This folder contains compiled data used for generating examples of apparent polar wander path inversions.

#### code_output
### pygplates

This folder contains output figures and data from the Jupyter Notebooks.
This folder contains the pygplates library which is licensed with a CC BY 3.0 license and distributed by the EarthByte group: https://www.earthbyte.org/category/resources/software-workflows/pygplates/

### Jupyter Notebooks

Jupyter notebooks within the main folder of the repository demonstrate the functions of the package, conduct analysis, and develop visualizations that are presented in the accompanying manuscript.

#### setting up Python environment
## Setting up Python environment

Conda users can use the _environment.yml_ file in the repository to generate a working Conda Python environment that can execute the code in this repository.

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