https://github.com/djpugh/mtfit
MTfit code for Bayesian Moment Tensor Fitting
https://github.com/djpugh/mtfit
bayesian double-couple fault-plane geophysics microseismic moment-tensor seismology source-inversion
Last synced: 7 months ago
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MTfit code for Bayesian Moment Tensor Fitting
- Host: GitHub
- URL: https://github.com/djpugh/mtfit
- Owner: djpugh
- Created: 2017-04-07T14:40:19.000Z (over 8 years ago)
- Default Branch: develop
- Last Pushed: 2022-06-21T21:14:35.000Z (over 3 years ago)
- Last Synced: 2025-02-28T08:46:02.087Z (7 months ago)
- Topics: bayesian, double-couple, fault-plane, geophysics, microseismic, moment-tensor, seismology, source-inversion
- Language: Python
- Size: 53.5 MB
- Stars: 79
- Watchers: 10
- Forks: 17
- Open Issues: 18
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Metadata Files:
- Readme: README.rst
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README
.. image:: https://travis-ci.org/djpugh/MTfit.svg?branch=develop
:target: https://travis-ci.org/djpugh/MTfit/
.. image:: https://ci.appveyor.com/api/projects/status/rvi74lcro7q3od85?svg=true
:target: https://ci.appveyor.com/project/djpugh/mtfit
The documentation is available at `https://djpugh.github.io/MTfit/ `_ and can be built using `sphinx` from the source in MTfit/docs/, or using the `build_docs.py`.
The documentation includes tutorials and explanations of MTfit and the approaches used.
Please note that this code is provided as-is, and no guarantee is given that this code will perform in the desired way. Additional development and support is carried out in the developer's free time.
**Restricted: For Non-Commercial Use Only**
This code is protected intellectual property and is available solely for teaching
and non-commercially funded academic research purposes.
Applications for commercial use should be made to Schlumberger or the University of Cambridge.
Installing MTfit
*********************************
MTfit is available on `PyPI` and can be installed using:
>>pip install MTfit
Alternative this repository can be cloned and the package then installed simply by calling::
>>python setup.py install
MTfit is dependent on numpy and scipy, and for MATLAB -v7.3 support also requires h5py.
Cluster support will be automatically installed via pyqsub from github
MPI support requires mpi4py built against a valid MPI distribution.
To build the C extensions when compiling from source you will need cython and associated C compilers
! Known Bug - running with MPI and very large non-zero MT results can lead to an error: mpi4py SystemError: Negative size passed to PyString_FromStringAndSize - to fix, re-run with smaller sample sizes