Exploring dynamic fitness landscapes

This repository is a bit chaotic, as the project has become a multi-year effort and my programming/organizational skills have evolved along with it. I used Python and Jupyter notebooks to do analysis and plotting. There is an implementation of the simulator in C++ that must be built into a Python module in order for the notebooks to run.

Dependencies

The main external dependencies are NumPy, pandas, Plotly, and Jupyter. My environment contains plotly==3.3.0 and Python 3.6.4. Newer versions of Plotly may break things.

Getting started

1. Make sure NumPy is installed in your environment.
2. Inside simulator-cpp, run python setup.py build.
3. Run python setup.py install, or move the resulting .pyd or .so from the build/lib.system directory into notebooks-py.
4. Use Jupyter Notebook or JupyterLab to view the notebooks in notebooks-py.

References

• Ogbunugafor, C., Eppstein, M. Competition along trajectories governs adaptation rates towards antimicrobial resistance. Nat Ecol Evol 1, 0007 (2017). https://doi.org/10.1038/s41559-016-0007
• Mira, P. M. et al. Rational Design of Antibiotic Treatment Plans: A Treatment Strategy for Managing Evolution and Reversing Resistance. PLOS ONE 10, e0122283 (2015). https://doi.org/10.1371/journal.pone.0122283