|
def | __init__ (self) |
|
def | Additive_Solve (self, problem, num_fidelity_levels=2, num_samples=10, max_iterations=10, tolerance=1e-6, opt_type='basic', num_starts=3, print_output=True) |
|
def | evaluate_model (self, problem, x, cons) |
|
def | evaluate_corrected_model (self, x, problem=None, obj_surrogate=None, cons_surrogate=None) |
|
def | evaluate_expected_improvement (self, x, problem=None, obj_surrogate=None, cons_surrogate=None, fstar=np.inf, cons=None) |
|
def | expected_improvement_carpet (self, lbs, ubs, problem, obj_surrogate, cons_surrogate, fstar, show_log_improvement=False) |
|
def | scale_vals (self, inp, con, ini, bnd, scl) |
|
def | initialize_opt_vals (self, opt_prob, obj, inp, x_low_bound, x_up_bound, con_low_edge, con_up_edge, nam, con, x_eval) |
|
def | unpack_constraints_slsqp (self, x, con_ind, sign, edge, problem, cons_surrogate) |
|
def | initialize_opt_vals_SLSQP (self, obj, inp, x_low_bound, x_up_bound, con_low_edge, con_up_edge, nam, con, x_eval, problem, cons_surr) |
|
def | initialize_opt_vals_SHGO (self, obj, inp, x_low_bound, x_up_bound, con_low_edge, con_up_edge, nam, con, problem, cons_surr) |
|
def | run_objective_optimization (self, opt_prob, problem, f_additive_surrogate, g_additive_surrogate) |
|