This code is for modeling macro-dispersion in random porous networks with temporal Markov models.

• Markov models in time for simulation dispersion in random porous networks
• The stencil method and the extended stencil method
• An implementation of correlated CTRW for benchmarking results

For details about the ideas and models used in this code please refer to Temporal Markov Processes for Transport in Porous Media: Random Lattice Networks

• First clone this repository.
• Add the parent directory of py_dp to your Python path. In linux you will need to add a line similar to export PYTHONPATH=$PYTHONPATH:/PATH_TO_PARENT_OF_py_dp to your ~/.bashrc file.
• Make sure you have Python2.7 along with Matplotlib, Numpy, Scipy, Cython and pyamg. All of these packages can be installed using pip. (e.g. pip install numpy).
• Complete Cython installations:
  • go to the dispersion directory: cd py_dp/dispersion/
  • compile the cython files using these commands:
    • python setup_count.py build_ext --inplace
    • python setup_convert.py build_ext --inplace

After the setup steps you can run sample_scripts/workflow_dispersion_in_random_network.py. This file includes all the steps necessary to generate the input data for a small 100x100 structured network, generating MC data, and model the data using Markov models.

Direct to network_paper/plot_scripts and run python network_paper_plots.py. The plots will be stored in the network_paper/plots folder.