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MCMTpy

About

🚨 The package is still undergoing development. We'll update at the end of July. 🚨

MCMTpy is a Python package designed for seismic source study. It provides functionality for focal mechanism inversion and source parameters analysis.

MCMTpy has mainly provided functions as:

  • Focal mechanism inversion of the double couple source and moment tensor using improved Markov chain Monte Carlo method.
  • A series of scripts is provided for source parameter calculation and conversion.
  • Moment tensor decompose, Huston plot and Beachball with station projected.

and it has the features as:

  • The package MCMTpy runs on Unix-like systems including Mac and Linux.
  • It has a close integration with Obspy, pyfk and pyasdf.
  • It can be done in parallel based on mpi4py.
  • It's is efficient to do the seismological research based on python.

./docs/figures/logo/logo-small-cut.png

Documentation

Detailed documentation can be found here.

Citation

If you use MCMTpy for your research and prepare publications, please citing MCMTpy:

  • MCMTpy: A Python Package for Source Parameters Inversion Based on Cut-And-Paste Algorithm and Markov Chain Monte Carlo. In prep for Seismological Research Letter.

Quick Installation

Firstly, make sure Anaconda has been installed, then:

$ conda create -n MCMTpy  python=3.8 numpy=1.16 matplotlib=3.1.1 mpi4py obspy pyasdf json5 tqdm
$ conda activate MCMTpy
$ pip install pyfk
$ pip install MCMTpy

Some errors may occurred of that pyfk not support the new version of cysignals, please:

$ conda uninstall cysignals
$ pip install cysignals==1.10.2
$ pip install pyfk

Successful installation will generate an executable program MCMTpy under the anaconda environment path: /Users/user/opt/anaconda3/bin. And run following code to check the installation:

$ MCMTpy --help

Short Tutorial

MCMTpy stores all the parameter information in four JSON files: build_GFs.json, syn.json, sample.json and plot.json, and you can find those json-files in path ./MCMTpy-master/jsons/. For parameters choosing, please refer to Detailed tutorial. The steps to do inversion process are:

1. Calculate green function database:

$ MCMTpy build_GFs pyfk  -c ./build_GFs.json
$ mpirun -n 4 MCMTpy build_GFs pyfk  -c ./build_GFs.json        # parallel

2. Synthesize the test data:

$ MCMTpy  syn pyfk  -c ./syn.json

3. Inversion of focal mechanism:

$ MCMTpy  sample MH  -c ./sample.json
$ mpirun -n 4  MCMTpy  sample MH  -c ./sample.json        # parallel

4. Result visualization:

$ MCMTpy plot pyfk -c plot.json

./docs/figures/station_location.png

./docs/figures/hist.png

./docs/figures/misfit.png

./docs/figures/alpha.png

./docs/figures/waveform.png

./docs/figures/beachball.png

./docs/figures/Decompose.png

License

MCMTpy is a free software: you can redistribute it and/or modify it under the terms of the MIT License. A copy of this license is provided in LICENSE.