v. 2021.03.20 for the latest version, please visit https://github.com/ekaestle
Author: Emanuel D. Kästle emanuel.kaestle@fu-berlin.de
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The following article should be cited by anyone who uses this code:
Kästle, E. D., Molinari, I., Boschi, L., Kissling, E., & AlpArray Working Group. (2022). Azimuthal anisotropy from Eikonal Tomography: example from ambient-noise measurements in the AlpArray network. Geophysical Journal International, 229(1), 151-170.
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The Python scripts can be used to apply isotropic and azimuthally anisotropic Eikonal tomography after Lin et al. (2009). Detailed instructions on the principles of the Eikonal method and how this code works are given in the article referenced above.
Python v.3.6 or above with the following packages: numpy, mpi4py, scipy, matplotlib, basemap, pyproj, cartopy optional: scikit-fmm, pillow (to use the fast-marching method and create synthetic data) recommended: spyder or another python editor
It is recommended to install Python and all required packages via Anaconda (executable installers and instructions for Linux/Windows/Mac can be found on the Anaconda webpage).
Once Anaconda is installed, create a new environment in a console window, for example: $ conda create -n py39 python=3.9 # or other supported Python version $ conda activate py39 # activate the newly created environment
Then, install all the required packages $ conda install numpy scipy matplotlib basemap pyproj cartopy mpi4py
The optional packages can be installed the same way $ conda install scikit-fmm pillow spyder=4
You should now be able to run the first example $ cd {path_to_this_folder}/synthetic_example_simple/ $ python eikonal_tomography.py
The input should be given as travel times between station pairs. An example input file is given in the synthetic_example_simple folder. The example dataset can be re-created with the provided script
$ python create_synthetic_data_simple.py
The creation of synthetic data requires that the FMM.py script is in the same folder.
The second synthetic example provided in the synthetic_example_publication/ folder re- creates the data presented in the above referenced article. Execution of this script will take very long. Finally, example_dataset_rayleigh.txt is created. The Eikonal tomography is applied by running
$ python eikonal_tomography.py
Inside the eikonal_tomography.py script, there is a header section with user-defined parameters. The function of these parameters is explained in the script itself and in the above-referenced article.
Prepare one or several input files according to the scheme explained at the top of the eikonal_tomography.py script (compare example datasets in the synthetic_example_.../ folders).
Copy the eikonal_tomography.py script to a new folder. Adapt all the parameters in the USER-DEFINED PARAMETERS section of the script to your needs.
Run $ python eikonal_tomography.py
The results will appear in a newly created subfolder.
In case of questions/problems, feel free to contact emanuel.kaestle@fu-berlin.de
Lin, F.-C., Ritzwoller, M. H., and Snieder, R. (2009). Eikonal tomography: surface wave tomography by phase front tracking across a regional broad-band seismic array. Geophysical Journal International, 177(3):1091–1110.