Teleseismic body wave modeling through stacks of (dipping/anisotropic) layers
This program generates sets of ray-theoretical seismograms for incident plane waves
(teleseismic approximation) for seismic velocity models consisting of a stack of layers
with planar but non-parallel (dipping) interfaces, allowing the possibility of anisotropy
in the layers. Incident P and S waves are supported.
PyRaysum is a Python wrapper around the Fortran software Raysum, originally developed by
Andrew Frederiksen.
A trimmed down version of the Fortran code is supplied with PyRaysum. You can find the
original version here.
Authors: Wasja Bloch, Pascal Audet (Developers and Maintainers of PyRaysum) & Andrew Frederiksen & (Developer of original Fortran version)
PyRaysum can be installed from PyPI or from source.
To avoid conflicts with other programs, it is recommended to install PyRaysum inside a designated conda environment (called here prs) alongside its dependecies.
conda create -n prs "python<3.12" "numpy<1.23" setuptools fortran-compiler obspy -c conda-forgeconda activate prs
If you are using an alternative Python interpreter (e.g., IPython or a Jupyter
notebook), include it into your installation as well. This ensures that the interpreter
uses the correct Python version.
# IPythonconda install ipython# Jupyter notebooksconda install jupyter
pip install pyraysum
The source code of PyRaysum can also be downloaded from GitHub and installed via pip.
git clone https://github.com/paudetseis/PyRaysum.gitcd PyRaysumpip install .
To compute receiver functions for a range of back-azimuths considering a simple 1-layer
over a half-space subsurface seismic velocity model, in a Python or iPython console, execute:
from pyraysum import Model, Geometry, Control, run# Build a 1-layer-over-half-space subsurface modelmodel = Model(thickn=[32000, 0], # m; half-space thickness is irrelevantrho=[2800, 3600], # kg/m^3vp=[6400, 8100], # m/svs=[3600, 4650], # m/s)model.plot()# Define back-azimuth range and single horizontal slowness valuegeometry = Geometry(baz=range(0, 360, 30), slow=0.07)geometry.plot()# Set sampling interval, number of points, alignment and ray-coordinate rotationcontrol = Control(dt=1./20., npts=800, align="P", rot="PVH")# Run the simulationresult = run(model, geometry, control, rf=True)# Filter below 2s periodresult.filter("rfs", "lowpass", freq=0.5)# Plot the resultsresult.plot("rfs")
The complete API documentation, scripts and tutorials are described at https://paudetseis.github.io/PyRaysum/
If you use PyRaysum in your work, please cite the following references:
Frederiksen, A.W., and Bostock, M.G. (2000) Modelling teleseismic waves in dipping anisotropic structures. Geophysical Journal International 141: 401-412. https://doi.org/10.1046/j.1365-246x.2000.00090.x
Bloch, W., and Audet, P. (2023). PyRaysum: Software for modeling ray-theoretical plane body-wave propagation in dipping anisotropic media. Seismica. https://doi.org/10.26443/seismica.v2i1.220
Audet, P., and Bloch, W. (2022). PyRaysum: Software for modeling ray-theoretical body-wave propagation. Zenodo. https://doi.org/10.5281/zenodo.7468301
All constructive contributions are welcome, e.g. bug reports, discussions or suggestions for new features. You can either open an issue on GitHub or make a pull request with your proposed changes. Before making a pull request, check if there is a corresponding issue opened and reference it in the pull request. If there isn’t one, it is recommended to open one with your rationale for the change. New functionality or significant changes to the code that alter its behavior should come with corresponding tests and documentation. If you are new to contributing, you can open a work-in-progress pull request and have it iteratively reviewed.
Other examples of contributions include notebooks that describe published examples of PyRaysum usage and processing. Suggestions for improvements (speed, accuracy, plotting, etc.) are also welcome.
