Sequences of Earthquakes and Aseismic Slip (seqeas) Python package

Code for the forward modeling part of the study "Probabilistic Estimation of Rheological Properties in Subduction Zones using Sequences of Earthquakes and Aseismic Slip" by T. Köhne, R. Mallick, and M. Simons, submitted to Geophysical Journal International.

Installation

git clone https://github.com/tobiscode/seqeas-public
conda create --name seqeas --channel conda-forge --override-channels --file seqeas-public/requirements.txt
conda activate seqeas
pip install ./seqeas-public

Documentation

An API documentation is generated into the docs folder. It is hosted on GitHub publicly at tobiscode.github.io/seqeas-public, but you can also read it locally, e.g., by running python -m http.server 8080 --bind 127.0.0.1 from with the documentation folder and then opening a browser. It is created using pdoc ./seqeas --math -o docs -d numpy.

Examples

These are the commands used to generate the target synthetic data for the different test cases. Running python generate_powerlaw_cases.py without any arguments shows an explanation of the script arguments.

2D: Power-law viscosity

All commands assume the user is in the examples folder.

Case (1)

python generate_powerlaw_cases.py ./2d_pl_case1/ 200 400 5 -25 -0.0034223 9130 0.01

Case (2)

python generate_powerlaw_cases.py ./2d_pl_case2/ --no-plot-faultvels --no-plot-faultslip --no-plot-eqvels --no-plot-fault --no-plot-phases --no-plot-viscosity --no-plot-viscosity_ts 200 400 5 -10.809 -0.0034223 3947 0.01

Case (3)

python generate_powerlaw_cases.py ./2d_pl_case3/ --no-plot-faultvels --no-plot-faultslip --no-plot-eqvels --no-plot-fault --no-plot-phases --no-plot-viscosity --no-plot-viscosity_ts 200 400 5 -10.77067 -0.0034223 3933 0.01

(The horizontal observations are still generated here, but then later ignored by the inversion step.)

Case (4)

Uses the data from case (3) with the modified ./2d_pl_case4/fault_subduction.ini for the inversion models.

Case (5)

Uses the data from case (1) with the modified ./2d_pl_case5/fault_subduction.ini for the inversion models.

2D: Rate-dependent friction

Uses the data from case (1) with the modified ./2d_rd/fault_subduction.ini for the inversion models.

AlTar integration

To run the inverse model (i.e., estimating the rheological parameters that were used to create the target synthetic data), any Markov chain Monte Carlo sampler can be used. In our case, we use the AlTar Framework which we have extended to incorporate the model of this Python package. This code can be found in the seas-devel branch, defined by the starting executable script being and model definition.

An example seas.pfg configuration file can be found in the folder of Example 1, and it can be used (once AlTar is installed) like this:

cd ./2d_pl_case1/
OMP_NUM_THREADS=1 SEAS --config=seas.pfg