Version 1.1.3, last update 23.11.2020 (Python version included)
Author
Václav Vavryčuk (vv@ig.cas.cz)
Short description
STRESSINVERSE is a Matlab or Python software package for an iterative joint inversion for stress and fault orientations from focal mechanisms. The Matlab code needs just the Matlab kernel and no toolboxes are required. Corresponding Python code requires matplotlib, numpy, scipy and os modules. The inversion is based on Michael’s method (1984, 1987) in which an instability criterion proposed by Lund & Slunga (1999) is incorporated.
Details about the method and its accuracy are presented in Vavryčuk (2014).
Primary reference
Vavryčuk, V., 2014. Iterative joint inversion for stress and fault orientations from focal mechanisms, Geophysical Journal International, 199, 69-77, doi: 10.1093/gji/ggu224.
Other references
Lund, B., Slunga, R., 1999. Stress tensor inversion using detailed microearthquake information and stability constraints: Application to Olfus in southwest Iceland, J. Geophys. Res. 104, 14.947-14.964.
Michael, A.J., 1984. Determination of stress from slip data: Faults and folds, J. Geophys. Res. 89, 11.517-11.526.
Michael, A.J., 1987. Use of focal mechanisms to determine stress: A control study, J. Geophys. Res. 92, 357-368.
Vavryčuk, V., 2011. Principal earthquakes:Theory and observations from the 2008 West Bohemia swarm, Earth Planet. Sci. Lett., 305, 290-296.
Vavryčuk, V., Bouchaala, F., Fischer, T., 2013. High-resolution fault image from accurate locations and focal mechanisms of the 2008 swarm earthquakes in West Bohemia, Czech Republic, Tectonophysics, 590, 189-195.
Download
Please fill in the following form. After submitting needed information you will be redirected to download. Both Matlab and Python versions are included in the zip file.
User guide
The software is structured in the following directories: Data, Documentation, Figures, Output, Programs.
Run the code
The stress inversion is run by a script called StressInverse.m in the Programs_MATLAB directory or StressInverse.py in the Programs_PYTHON directory.
Control parameters
Parameters controlling the inversion are defined in the script called Data/input_parameters.m or Programs_PYTHON/Input_parameters.py. The main control parameters are:
- input_file (the name of the input data),
- output_file (the name of the file with the results),
- principal_mechanism_file (the name of the file with calculated principal focal mechanisms),
- N_noise_realizations (number of realizations of random noise for accuracy estimates),
- mean_deviation (estimate of accuracy of input focal mechanisms in degrees).
Input data
Input focal mechanisms should be stored in the Data directory. The conjugate solutions can be mixed randomly. The strike and dip angles need not describe the orientation of true fault planes.
The name of the input file is defined in input_parameters.m (or Input_parameters.py).
The input data are formed by three columns:
- strike (1st column), dip (2nd column), rake (3rd column).
Output
Two output files are stored in the Output directory. They have an extension ‘.mat’ and ‘.dat’.
The ‘.mat’ output file includes:
sigma_1, sigma_2 and sigma_3 (azimuth and plunge of principal stress directions),
shape ratio,
mechanisms (strike, dip and rake of focal mechanisms with a correctly selected fault plane),
principal_mechanisms (strike, dip and rake of two principal focal mechanisms found for the retrieved optimum stress tensor),
friction (mean friction on the faults).
The ‘.dat’ output file is the ASCII file and contains three columns with:
- strike, dip, rake
These angles describe the focal mechanisms with fault orientations determined by the code.
Additionally, an ASCII file with two principal focal mechanisms calculated for the found optimum stress tensor is created. The file contains two rows (each row for one principal focal mechanism) with the following angles:
- strike, dip, rake
Figures
Figures are stored in the Figures directory.
The code generates the following figures:
- P_T_axes.png (focal sphere with the P and T axes and with the optimum principal stress axes),
- Mohr_circles.png (Mohr’s circles with fault planes),
- stress_directions.png (confidence limits of the principal stress axes),
- shape_ratio.png (histogram of the shape ratio).
Example
As an example, we provide the input file called ‘West_Bohemia_mechanisms.dat’ with focal mechanisms from the West Bohemia swarm area (for the analysis of these data, see Vavryčuk 2014). The output files are called ‘West_Bohemia_output.mat’, ‘West_Bohemia_output.dat’ and ‘West_Bohemia_principal_mechanisms.dat’.
To run the inversion just call ‘StressInverse.m’ in Matlab or ‘StressInverse.py’ in Python.
Python code
The Python codes are saved with DOS newlines (CRLF), you can use _dos2linux.sh code to convert them to have Unix newlines (LF).
You need to have installed these python libraries:
matplotlib, numpy, scipy, os
Codes were tested on both Windows and Linux systems, Python 2.7 and 3.5, Python and IPython shells.
Copyright
The code can be freely used for research purposes. In the case of publishing the results obtained by this code, please, refer to the paper of Vavryčuk (2014). If you intend to use the code for commercial purposes, you should contact the author (vv@ig.cas.cz) for providing with the commercial licence. The use of the software for commercial purposes with no commercial licence is prohibited.