External packages

GemPy

To use implicit geological models inside the sandbox, go to GemPy, clone or download the repository and follow the GemPy Installation instructions. With GemPy installed you can follow the tutorial GempyModule:

pip install gempy

If using windows you will need to install Theano separately as instructed in here:

conda install mingw libpython m2w64-toolchain
conda install theano
pip install theano --force-reinstall

Devito

This package uses the power of Devito to run wave proppagation simmulations. More about this can be found in notebooks/tutorials/10_SeismicModule/. Follow the Devito installation instructions. This module so far have only support in Linux:

pip install --user git+https://github.com/devitocodes/devito.git

PyGimli

This library is a powerful tool for geophysical inversion and modelling. Some examples can be found in notebooks/tutorials/11_Geophysics/. PyGimli can be installed following the installation intructions here. We recomend creating a new environment where PyGimli is already installed and over that one install the sandbox dependencies:

conda create -n sandbox-env -c gimli -c conda-forge pygimli=1.1.0

And now go back to installation and follow all over again the instruction but skipping step 2:

PyTorch

To use the LandscapeGeneration module we need to install PyTorch. This module use the power of CycleGAN to take a topography from the sandbox, translate this as a DEM and then display it again on the sandbox as a Landscape image. To install the dependencies for this module do:

• For Windows:

  pip install torch===1.6.0 torchvision===0.7.0 -f https://download.pytorch.org/whl/torch_stable.html
  

• For Linux:

  pip install torch torchvision
  git clone https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
  cd pytorch-CycleGAN-and-pix2pix
  pip install -r requirements.txt
  

Once this is installed, copy the trained model in /notebooks/tutorials/09_LandscapeGeneration/checkpoints folder, and then follow the notebook. Get in contact with us to provide you with the train model for this module.