Ground motion simulation in time-frequency domain based on conditional generative adversarial network and phase retrieval approaches.
Used as command line application, TFCGAN can be used to create .npy files of synthetic seismic waveforms using a pre-trained ANN model.
Install python 3.10.0 (anaconda or venv), then:
Standard install:
pip install --upgrade pip setuptools && pip install .
Developers install (install editable package and tests libraries):
pip install --upgrade pip setuptools && pip install -e ".[dev]"
In the Python virtualenv and then:
Check versions: pip freeze should give tensorflow==2.11.1 and numpy==1.26.1
For developers, run tests via pytest ./tests
TFCGAN is a command line application to be launched from the terminal. For help,
type tfcgan --help in your terminal
TFCGAN can also be used in your Python code (disclaimer: the snippet below has not been tested, please provide feedback in case of import errors):
from tfcgan.tfcgan import TFCGAN
# setup your parameters. Example:
mag = 7
dist = 100
vs30 = 760
num_waveforms = 10
# Generate waveforms, time and frequencies:
tfc = TFCGAN().maker(mag, dist, vs30, num_waveforms)
# get waveform data:
data = tfc[-1]
# data is a Numpy Matrix of shape (num_waveforms, 4000).
# Each waveform delta time is 0.01 sec
# (i.e., each waveform is 40s long by default)- create model with tensorflow 12.16 or whatever,
- create models in hdf format (see tensorflow doc)
- check the running code by running the tests