Prepare the script that will generate all data

[MichalisPanayides]

Added a function in models.py that checks which of the three scenarios (of Theorem 1 of the paper) a particular set of parameters falls into. The function returns:

• True if we hit steady state
• False if we don't hit steady state
• None if we don't know

Also, main.py in the experiments/ directory contains the initial version of the script

[MichalisPanayides]

@geraintpalmer I think this is done now ✔️

Still needs to be parallelised and maybe a 3-class version 👍

[MichalisPanayides]

@geraintpalmer The 2-class simulation experiments should be good to go. For the 2-class Markov experiments we need to decide on some values for the hyper parameters (initial_bound, final_bound, step_bound, epsilon).

Have not implemented 3-class scripts yet.