smt_optim.utils package# Submodules# smt_optim.utils.constraints module# compute_rscv(cstr_values: ndarray, cstr_configs: list) → ndarray[source]# compute_rscv_sp(x: ndarray, cstr_list: list[dict]) → float[source]# SciPy wrapper to compute the Root Squared Constraint Violation (RSCV). Parameters: x cstr_list Returns: smt_optim.utils.get_fmin module# get_fmin(f: ndarray, c: ndarray | None = None, c_type: list[str] | None = None, rscv_tol: float = 0.0) → float[source]# smt_optim.utils.initial_design module# generate_initial_design(state: State, evaluator, config) → None[source]# smt_optim.utils.json module# json_safe(obj)[source]# smt_optim.utils.logger module# class ConsoleLogger(config)[source]# Bases: object on_iter_end(state) → None[source]# print_header()[source]# class JsonLogger(config)[source]# Bases: object on_iter_end(state) → None[source]# format_value(v, fmt)[source]# smt_optim.utils.plot_2d module# get_plot2d_data(func: Callable, bounds: ndarray, num_points: int = 101) → tuple[source]# smt_optim.utils.stop_criteria module# check_stop_criteria(state, config) → bool[source]# compute_budget(state) → float[source]# Module contents#
