This repo was created in an attempt to reproduce the plots shown at the kickoff of the AstroTOM ("Turing or Milankovitch") project by Niklas Hohmann, from his Matlab scripts (available at github.com/MindTheGap-ERC/LMA-Matlab).
AstroTOM is an OpenSSI 2021b project from the Netherlands eScience Center and Utrecht University (UU).
Dr. Emilia Jarochowska (UU) is the lead applicant of this project.
After replacing central differencing for the gradients in the five diagenetic equations 40-43 from L'Heureux (2018) by forward and backward differencing depending on the sign of U and W as a first step and a Fiadeiro-Veronis spatial difference scheme as a second step, it turns out that these equations can be integrated for more than 13.190 years (the full T*) with an implicit or explicit (in time) solver, but not with a simple Eulerian scheme. A Runge-Kutta solver, with an adaptive timestep will, however, suffice. After correcting the value of b (5-->5e-4) it turned out that a stable integration is also possible without a Fiadeiro-Veronis scheme. We currently make use of a constant porosity diffusion coefficient.
The implicit (in time) solvers that solve_ivp offers can be deployed with its numerically approximated Jacobians and a Jacobian sparsity matrix.
Wide use is made of the py-pde package, especially CartesianGrid and ScalarField.
To run this code, you need git and conda or pip to install .
git clone [email protected]:astro-turing/Integrating-diagenetic-equations-using-Python.git
or
git clone https://github.com/astro-turing/Integrating-diagenetic-equations-using-Python.git
Next,
cd Integrating-diagenetic-equations-using-Python
pipenv install
For the latter command you need pipenv which you can install
using either
pip install pipenv
or
conda install -c conda-forge pipenv.
Now you may be running into certain Python version requirements, i.e. the Pipfile requires a Python version that you do not have installed. For this conda can help, e.g.:
conda create -n py311 python=3.11 anaconda to create a Conda Python 3.11 environment.
You can use that freshly installed Python version and possibly any additionally installed libraries - using the --site-packages argument - by executing pipenv install --python=$(conda run -n py311 which python) --site-packages --skip-lock. The latter argument - --skip-lock - may be redundant, but if your previous pipenv install failed, pipenv --rm may be needed.
After a succesful pipenv installation you should be able to execute
pipenv run python marlpde/Evolve_scenario.py
or
pipenv shell
python marlpde/Evolve_scenario.py
Results in the form of an .hdf5 file will be stored in a subdirectory of a Results directory, which will be in the root folder of the cloned repo.
If you prefer poetry over pipenv, you may install all the dependencies and activate the environment using the command poetry install. Next, either:
poetry run python marlpde/Evolve_scenario.py
or
poetry shell
python marlpde/Evolve_scenario.py
From the root folder, i.e. the folder you enter after cd Integrating-diagenetic-equations-using-Python, either run
pipenv run python -m pytest
or
poetry run python -m pytest
Copyright 2023 Netherlands eScience Center and Utrecht University
Funded by the European Union (ERC, MindTheGap, StG project no 101041077). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them.
