rsr.rsr.minimise_upper_states_random

rsr.rsr.minimise_upper_states_random(comps_st, sfun, sys_upper_st, *, fval=None, min_state=0, step=1, seed=None, exclude_keys=('sys',))[source]

Random greedy reduction of component states.

Algorithm (given a random permutation of components):

  • Try lowering each component by step (e.g., 1).

  • Call sfun(modified_state). Expect sfun to return a tuple where the 2nd element is int that represents a system state.

  • If status >= sys_upper_st: keep the lowered value and continue cycling. If the component reaches min_state, remove it (can’t lower further).

  • If status < sys_lower_st: revert the change and remove that component (no further attempts).

Stops when all components have been removed from the candidate pool.

Returns:

  • final_state: dict of the minimised states.

  • info: dict with keys permutation, removed_on_lower, hit_min_state, attempts.

Return type:

Tuple (final_state, info)