lsforce is a Python-based single-force seismic inversion framework for massive landslides. The codes can also be applied to other seismic sources that are well-approximated as a single force (e.g., volcanic eruptions, some glacial events). The library can be used to invert long period (tens to hundreds of seconds) seismic waveforms to estimate a time series vector of single forces that represents the equivalent forces exerted on the Earth by the landslide (see example output figure below).
The following has only been tested on macOS.
Clone this repo and run the installation script, which creates an environment named
lsforce
and installs the lsforce package into the environment:
git clone https://code.usgs.gov/ghsc/lhp/lsforce.git
cd lsforce
bash install.sh # Or `bash install.sh 1` if you want developer tools as well
The install script will check if you have the
conda
or
mamba
package managers installed. If you
have both installed, it will use mamba
. If you have neither installed, it will install
mamba
and then use it. If you only have conda
installed, we strongly recommend
that you install mamba
before running the install script. mamba
is much, much faster
than conda
when solving the lsforce
environment.
By default, the Green's functions used by lsforce come from the Synthetics Engine (Syngine) hosted by IRIS Data Services. The user can choose from a fixed set of 1D Earth models.
Alternatively, if users prefer to compute Green's functions using a custom model (see Documentation), they can optionally install Computer Programs in Seismology (CPS) via the following:
- Install GCC with e.g. Homebrew:
brew install gcc
- Complete the CPS license form, download the resulting archive, and unzip
- Move the directory
PROGRAMS.330
to where you'd like to install, then:cd PROGRAMS.330 ./Setup OSX40 ./C
- Add the executables to
PATH
by adding the following line to e.g.~/.bash_profile
:export PATH="$PATH:/path/to/PROGRAMS.330/bin"
Documentation for lsforce is visible online here.
To build the interactive HTML documentation yourself, first ensure that you installed
the developer tools (bash install.sh 1
), which are required for documentation
building. Then:
conda activate lsforce
cd doc
make html
open _build/html/index.html # macOS command to open file in browser
(To build Markdown documentation, use make markdown
.)
The lsforce package includes a script,
axisem2cps
,
which can convert 1D Earth models from Syngine into CPS model files. These models can
then be further modified for specific use cases. In addition, completely custom CPS
model files can be provided; for more information on CPS model files, see Chapter 8 of the
CPS documentation. The
lsforce
conda environment must be active for the script to be available.
Usage examples for the two currently-supported parameterization methods are given in the
three Jupyter Notebooks example_full.ipynb
,
example_triangle.ipynb
, and example_lamplugh.ipynb
, which are located in the
notebooks
directory. To open the notebooks, run:
conda activate lsforce
jupyter notebook notebooks
This will start a Jupyter Notebook server and open a new window or tab in your browser with the interactive notebooks displayed.
The primary host for the development of this software is on code.usgs.gov (GitLab) here:
One drawback of the USGS GitLab is that it's more cumbersome for external users to create an account and post issues than on GitHub. Hence, we've made a mirror of this repository on GitHub here:
If you have a GitHub account, you can immediately post issues to this mirrored repository.
Tests are located in the tests
directory. To run the tests, first ensure that you
installed the developer tools (bash install.sh 1
), which are required for testing.
Then:
conda activate lsforce
pytest
Allstadt, K. E., Toney, L., & Collins, E. A. (2023). lsforce (Version 1.1) [Source code]. U.S. Geological Survey Software Release. https://doi.org/10.5066/P9CR20KW
Toney, L., & Allstadt, K. E. (2021). lsforce: A Python-based single-force seismic inversion framework for massive landslides. Seismological Research Letters, 92(4), 2610–2626. https://doi.org/10.1785/0220210004