pyBEL1D

pyBEL1D is a python implementation of the BEL1D matlab codes (BEL1D). It is a work under devellopment and not in any form a finished product.

Installation:

The following instructions are working on Windows 10.

Build a new conda environment with python 3.7.

conda create -n bel1d
conda activate bel1d

Install the different libraries in the new environment:

conda install python=3.7.6 # For the python version
conda install numpy
conda install scipy
conda install scikit-learn
conda install matplotlib
conda install -c anaconda dill

# For multiprocessing:
pip install pathos

# For the sNMR application
conda config --add channels gimli --add channels conda-forge
conda install pygimli

# For DC application:
conda install libpython
conda install -c msys2 m2w64-toolchain
pip install git+https://github.com/miili/pysurf96

For MACOS installation, replace the last 3 lines with (not tested):

conda install -c anaconda gfortran_osx-64
pip install git+https://github.com/miili/pysurf96

On Linux machines run (not tested):

conda install -c anaconda gfortran_linux-64
pip install git+https://github.com/miili/pysurf96

For FWSW (full wavefield surface wave) application:

1 - composti:

We refer to the github of Matti Niskanen composti and recommend to follow the installation steps suggested therein.

2 - swprocess:

For further information, see the github of Joseph P. Vantassel swprocess.

pip install swprocess

Then run the code in this environment (composti for the example above).

Utilization

All the functions must be in the pyBEL1D folder to run (or you need to import the library, not yet implemented) and respect the folder architecture that is in the repository.

• The file MASW_paper.py containes a highely detailed and commented exemple on how to run BEL1D with IPR and post-process the results.
• The file exampleSNMR.py provides a commented example on how to run the codes for SNMR data.
• The file exampleDC.py provides an example on how to use BEL1D with a dispersion curve originating from real data.
• The file FWSW_synthetic-example.py provides an application of a synthetic benchmark for dispersion image creation by full wavefield transform and BEL projection.
• The file FWSW_field-example.py provides a field data application (download S2_field-data.ascii) for dispersion image creation by full wavefield transform and BEL projection.

Acknowledgements

The forward model for sNMR is provided by pygimli.

The forward model for Surface Waves dispersion curves is a Python inteface of the Computer programs in seismology (R. Hermans) provided by miili on github.

The forward model for Scholte wave dispersion is provided by R. Wang on MSEISFK08.