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#Max Veit's Undergraduate Thesis Project# ##Python implementation##

The implementation of the weighted-ensemble SSA with delays consists of three Python modules:

  • ssad.py
  • ensemble.py
  • util.py

and two scripts:

  • runner_wegen.py
  • runner_ddjd.py

The module ssad contains the full implementation of the SSA incorporating delayed reactions. The module ensemble, which depends on ssad, adds weighted-ensemble capability. A utility for generating a joint probability distribution is currently the only function in util.

The two scripts are for automated, i.e. non-interactive, execution of the algorithms for runs that take a long time or use lots of memory. More details below.

Much of the development and testing of the code, as well as generation, analysis, and plotting of results, was done using four IPython notebooks:

  • Testbed.ipynb, a sandbox notebook used for some of the inital testing as well as trying out new features and concepts.

  • UnitTesting.ipynb for more systematic testing of specific units of functionality (I may replace this with a formal set of tests using the unittest module at some point, although the stochastic nature of some of the algorithms makes precise unit testing difficult).

  • DelayedDegradation.ipynb, a detailed investigation of the delayed protein degradation system.

  • Plotting.ipynb for making nicely formatted plots of results generated by the automated scripts.

###Automated runner scripts###

The two scripts with names beginning with runner are for automated execution of the SSA and weighted-ensemble algorithms. They read in parameters from JSON files and write out the results in NumPy zipped format, so they do not require an interactive session to use.

The script runner_wegen.py is designed to read in an arbitrary set of reaction pathways and simulate them using the weighted-ensemble SSA. It uses a uniform paving for the bins used by the weighted-ensemble method. It records the probability distributions at the end of the dynamics time; multiple ensembles (with identical parameters) can be run in one job.

The script runner_ddjd.py is specialized to the delayed protein degradation system. It sets up the system, runs it for multiple values of a certain parameter (the delayed degradation rate $C$), and generates a delayed joint probability distribution $P(n(t) = p, n(t - \tau) = q)$ for each parameter set.

Parameters for the scripts are stored in JSON files, one parameter set per file. The individual parameters are not documented, but the files params/ddwe_gauss_t1_wa800_res.json (for use with runner_ddwe.py) and params/ddjd_csweep3_wa100.json as well as params/ddjd_csweep4_wa100.json (for runner_ddjd.py) provide examples of how these parameters are used. For the example parameter files included in the params directory, the filenames prefixed ddwe and pdwe are for use with the script runner_wegen.py and those prefixed ddjd are for use with runner_ddjd.py. Using a parameter set with the wrong script will result in various KeyErrors.

###Parallel Execution###

The codebase is currently entirely serial. The only method of parallelism available is system-level (i.e. running multiple jobs). I may add application-level parallelism at some point.