cGM-GANO

The repository contains code for Broadband Ground Motion Synthesis via Generative Adversarial Neural Operators: Development and Validation (also available on arxiv) , for more information about GANO implementation, please refer to GANO

Installation

create conda environment and install necessary libraries

conda create --name gano

conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia

conda install -c anaconda ipykernel

pip install ipykernel

python -m ipykernel install --user --name=gano

conda install pandas

conda install matplotlib
 
pip install scipy

pip install tqdm

pip install opencv-python

pip install cvxpy

Load the pretrained model

please download the trained model through following link, and store the model under kik_net_trained_model folder https://drive.google.com/file/d/18k366Y4UmaGoYxepwzZaGo_nw6Kup0cW/view?usp=sharing

Quick start of using trained GANO

run tutorials_for_cGmGANO.ipynb file for generating 3C waveforms

Train your own cGM-GANO

run train_GANO.ipynb