GDTchron: Geodynamic Thermochronology

About

GDTchron is a Python package for using the outputs of geodynamic models to predict thermochronometric ages.

Current authors:

Dylan Vasey
Peter Scully
John Naliboff
Sascha Brune
Ryan Stoner

Source code: https://github.com/dyvasey/gdtchron

Online documentation: https://gdtchron.readthedocs.io/en/latest/

The documentation consists of Jupyter Notebooks demonstrating use of the code and the full API for the code.

Installation

The latest release of GDTchron can be installed from PyPI or conda-forge using pip or conda as package managers:

# PyPI
pip install gdtchron

# conda-forge
conda install -c conda-forge gdtchron

For the latest development version, you can clone and install the GitHub repository with the source code. This repository also includes all the tests and Jupyter Notebooks.

git clone https://github.com/dyvasey/gdtchron.git
cd gdtchron
pip install .

Once installed, GDTchron can be used like any other Python package in scripts or Jupyter Notebooks.

Running GDTchron with Binder

Clicking the Binder badge at the top of this README will launch an interactive JupyterLab environment hosted by Binder with GDTchron installed. This is a good way to try out the functionality of GDTchron without needing to deal with a local Python installation. Note that the Binder environment does not have ASPECT installed.

Running GDTchron with ASPECT via Docker

Included in this repository is a Dockerfile allowing you to create an interactive JupyterLab environment that can run both ASPECT and GDTchron in Jupyter Notebooks. This environment allows you to fully run an accompanying ASPECT exhumation model, process it using GDTChron, and plot the results using the Jupyter Notebooks in the aspect directory. Note that fully replicating this process may take several hours.

See here for how to install Docker: https://docs.docker.com/get-started/

To build the environment, first ensure Docker is running. Then, from the repository root directory run:

docker build -f aspect/Dockerfile -t aspect-docker .

This may take a few minutes. To then run the environment:

docker run --rm --name aspect-docker -d -p 8888:8888 aspect-docker

The build and run commands are also provided in the shell script aspect/aspect_docker.sh

Once the environment is running, navigate to http://localhost:8888 in your browser.

To stop the environment, run:

docker stop aspect-docker

Note that the --rm flag in docker run means that the environment (including all files saved in it) will be removed once stopped (including if the session running the environment is ended). You can make it possible to restart the environment by omitting this flag, but this means that you will have to remove the environment manually when you are done with it.

To replicate the ASPECT uplift model and its results, run in order run_aspect_model.ipynb, process_model.ipynb, and figures_model.ipynb. The outputs of these are currently saved in the notebooks and viewable in the documentation.

Jupyter Notebooks

There are additional Jupyter Notebooks in the notebooks directory and displayed in the documentation demonstrating the functionality of GDTchron. Some of these notebooks can be directly replicated with just a GDTchron install (or in the Binder environment), whereas others depend on local output model files that are too large to include in this repository and are displayed as demonstrations only.

Fully Reproducible with GDTchron Install or Binder

tchron_demo.ipynb
scaling_test.ipynb

Not Reproducible without Large Size Local Files

process_riftinversion.ipynb
figure_riftinversion.ipynb
interpolation_comparison.ipynb

The ASPECT parameter files needed to reproduce the rift inversion model for these notebooks are available in the ri_prms directory.

Contributing to GDTchron

GDTchron is designed to be a community-driven, open-source Python package. If you have code you would like to contribute, please see the contributing guidelines.

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