have a proper control of the parameter runs entered by the configuration files

[lmoffatt]

First we will list all the parameters of the configuration files

Second list possible new parameters that might be important.

Third discuss the parameterization how should it be (for instance should we express as times the number of parameters or in iterations)

[lmoffatt]

write_script(script_name=runIdName)

thermo_algorithm = set_ThermoAlgorithm (num_scouts_per_ensemble = num_scouts_per_ensemble, number_trials_until_give_up = 100000, stops_at = 1e-18, beta_upper_value = 1e-2, beta_medium_value = 1e-6, includes_zero = 1, max_iter_equilibrium = max_iter_equilibrium, beta_size =beta_size, beta_upper_size = beta_upper_size, beta_medium_size=beta_medium_size, thermo_jump_factor = 4, save_every_param_size_factor=1)

thermo_evidence(idname= runIdName, model = model, prior= prior_model_name, likelihood_algorithm= likelihood_algorithm, data = observations, experiment = experiment_file, thermo_algorithm= thermo_algorithm, save_every =1, init_seed =0)

likelihood_algorithm = set_Likelihood_algorithm(adaptive_aproximation= 0, recursive_approximation= 1, averaging_approximation=2, variance_correction_approximation= 1, variance_approximation =0, n_sub_dt =1000)

[lmoffatt]

parameters to check:

thermo_jump_factor = 4, save_every_param_size_factor=1 save_every =1

[lmoffatt]

So, the idea is to set the thermo_jump_factor in iterations and calculate it at the script level. For that we need to implement ways to measure the number of steps in experiments, number of parameters and states for models and schemes and the number of beta and walkers.