Code for the manuscript:

Yarden Katz and Michael Springer, "Probabilistic adaptation in changing microbial environments", PeerJ (2016).

This code depends on the following external libraries:

• ParticleFever library
• libRoadRunner (with Python wrapper). This library can be simply installed by downloading pylibroadrunner for your platform and installing it like an ordinary Python package.

Once these libraries are installed, the code for the paper can be installed as a regular Python package using pip install . in the repository directory (or python setup.py install). Unit tests can be run using:

cd ./paper_metachange
python testing.py

The directories are organized as follows:

1. paper_metachange: Python module containing code used in paper
2. data: growth rate data
3. sbml_models: biochemical model from paper in SBML (.xml) format
4. simulations_params: parameters used for simulations
5. nonpython_figures: figures generated outside of Python

Figures are generated using a ruffus pipeline by running:

cd paper_metachange
python make_paper.py

Particle filtering inference for Bayesian models is done using the ParticleFever library.