|
5 years ago | |
---|---|---|
.idea | 5 years ago | |
docs | 5 years ago | |
examples | 5 years ago | |
extras | 7 years ago | |
maintenance | 6 years ago | |
src | 5 years ago | |
test | 5 years ago | |
.gitignore | 5 years ago | |
AUTHORS.md | 6 years ago | |
Docu_start.md | 6 years ago | |
LICENSE | 7 years ago | |
LICENSE.md | 6 years ago | |
README-dev.md | 5 years ago | |
README.md | 6 years ago | |
requirements.txt | 6 years ago | |
setup.cfg | 6 years ago | |
setup.py | 5 years ago |
README.md
Grond
Introduction
Grond explores characteristics of earthquake and deformation sources. It is a framework to search model spaces in non-linear inversion problems. A variety of source models and geophysical observations can be incorporated. Grond is not limited to a specific optimisation algorithm. The default optimizer in Grond is a global Monte Carlo sampler, capable of retrieving multimodal and irregularly shaped solution spaces. It is a multi-objective function optimizer and can efficiently apply the Bayesian bootstrap to estimate earthquake source model uncertainties. As foundation the Pyrocko toolbox is used.
Enabled source types so far are centroid moment tensors, double-couple point-sources and finite rectangular sources. Enabled data sets to be used for the inverse modelling are seismic waveforms, InSAR coseismic near-field displacement maps and GNSS coseismic displacement vectors. These data sets can used also combined. For seismic waveforms standard data formats can be used. For using coseismic InSAR displacement maps, a [Kite] InSAR data container needs to be prepared. Kite is an interactive InSAR-data post-processor, which imports a lot of standard InSAR processor output formats. For using GNSS campaign coseismic displacement vectors, a simple data file needs to be prepared, containing the GNSS station positions, displacement values and measurement uncertainties.
For the forward modelling precalculated and stored Green's functions are used. These stores can be obtained from an online repository or are user-defined and user-calculated using Pyrocko's fomosto module.
Installation
First, install Pyrocko, then install Grond:
git clone https://gitext.gfz-potsdam.de/heimann/grond.git
cd grond
sudo python setup.py install
For support of InSAR data modelling install also Kite
Updating an existing installation
cd grond # change to the directory to where you cloned grond initially
git pull origin master
sudo python setup.py install
License
GNU General Public License, Version 3, 29 June 2007
Copyright © 2018 Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany and University of Kiel, Kiel, Germany.
Grond is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. Grond is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.
Documentation
Find the documentation at https://pyrocko.github.io/grond/.
Community and support
Please use the Pyrocko Hive for discussion, feedback and bug reports.