This directory contains the scripts for computer simulation 2 
(performance dependence on noise level) from 

	Legenstein R, Pecevski D, Maass W 2008 A Learning Theory 
    for Reward-Modulated Spike-Timing-Dependent Plasticity with 
    Application to Biofeedback. PLoS Computational Biology 4(10): e1000180, Oct, 2008 
    
The produced result is supplementary figure 6.

To create these figures you need to:

1. The simulation performs 9 runs of the same experiment, possibly on different machines 
   in parallel. To change the names of the machines where the experiments should run, edit 
   the start_simulation.py file. The default values are cluster1 to cluster9.  
   
2. Execute:

    start_simulation.py
    
    This is an executable file, you don't need to run 'python start_simulation.py'.
    The program will create a new directory where the output files will reside. 
    
    Wait until the simulation finishes. You can monitor the simulations in the sim[0-8].out
    files in the newly created directory.
    

3. Then, to create supplementary figure 6 run:
   
      ipython -pylab figure_noise_levels.py