This is a moderately revamped version of the original PyVoroTomo by Fang et al. (2020). This code implements a Poisson Voronoi-based seismic traveltime tomography method, primarily suited for regional or smaller study areas but may also be expanded to do joint teleseismic inversions. PyKonal (White et al., 2020) is used for calculating traveltimes and tracing rays.
Easiest to clone into your directory:
$ git pull https://github.com/filefolder/PyVoroTomo.git
and install locally via pip, $ python -m pip install ./PyVoroTomo
... which will install the pyvorotomo executable
See also: https://github.com/malcolmw/PyVoroTomo/wiki/Installation
Depending on your model complexity and catalog size, it may be best to run via openmpi.
$ mpiexec -n 56 pyvorotomo -r -c experiment.cfg ./catalog.h5 ./stations.h5 -s /dev/shm
parameters:
-n number of CPU
-r relocate catalog first (highly recommended)
-c /path/to/configfile.cfg
-o output directory (default is ./output_YYYYMMDDTHHMMSSS)
-l logfile (default is outputdirectory/pyvorotomo.log)
-s scratch dir (recommend /dev/shm or some other ram partition for speed)
-t only run the sensitivity test
-v enable verbose/debug logging
-x output all realizations
OTHERWISE, simply run via $ pyvorotomo -r -c experiment.cfg ./catalog.h5 ./stations.h5 -s /dev/shm
Python3.14 is also recommended for individual multicore machines (supported soon! instructions then!)
see examples for available options, explanations and recommendations!
bin: Where the python executable pyvorotomo lives
pyvorotomo: Module code. The main one you probably want to look at is _iterator.py
scripts: Some tools to generate stations.h5, catalog.h5, and other common tasks (work in progress)
synth_data: Some synthetic data to experiment with
real_data: Some example real-world data
If you make use of this code in published work, please cite the below (more very soon I expect :)
Refer to https://github.com/malcolmw/PyVoroTomo/wiki/Installation for both laptops and clusters.
- Fang, H., van der Hilst, R. D., de Hoop, M. V., Kothari, K., Gupta, S., & Dokmanić, I. (2020). Parsimonious seismic tomography with Poisson Voronoi projections: Methodology and validation. Seismological Research Letters, 91(1), 343-355.
- White, M. C. A., Fang, H., Nakata, N., & Ben-Zion, Y. (2020). PyKonal: A Python Package for Solving the Eikonal Equation in Spherical and Cartesian Coordinates Using the Fast Marching Method. Seismological Research Letters, 91(4), 2378-2389. https://doi.org/10.1785/0220190318