discrete_optimization.generic_tools.result_storage package

Submodules

discrete_optimization.generic_tools.result_storage.multiobj_utils module

class discrete_optimization.generic_tools.result_storage.multiobj_utils.TupleFitness(vector_fitness: ndarray, size: int)[source]

Bases: object

distance(other: TupleFitness) → floating[source]
size: int
vector_fitness: ndarray

discrete_optimization.generic_tools.result_storage.result_storage module

class discrete_optimization.generic_tools.result_storage.result_storage.ParetoFront(list_solution_fits: List[Tuple[Solution, float | TupleFitness]], best_solution: Solution | None, mode_optim: ModeOptim = ModeOptim.MAXIMIZATION, limit_store: bool = True, nb_best_store: int = 1000)[source]

Bases: ResultStorage

add_point(solution: Solution, tuple_fitness: TupleFitness) → None[source]
compute_extreme_points() → List[Tuple[Solution, TupleFitness]][source]
finalize() → None[source]
len_pareto_front() → int[source]
class discrete_optimization.generic_tools.result_storage.result_storage.ResultStorage(list_solution_fits: List[Tuple[Solution, float | TupleFitness]], best_solution: Solution | None = None, mode_optim: ModeOptim = ModeOptim.MAXIMIZATION, limit_store: bool = True, nb_best_store: int = 1000)[source]

Bases: object

add_solution(solution: Solution, fitness: float | TupleFitness) → None[source]
property best_fit
best_solution: Solution | None
finalize() → None[source]
get_best_solution() → Solution | None[source]
get_best_solution_fit() → Tuple[Solution, float | TupleFitness] | Tuple[None, None][source]
get_last_best_solution() → Tuple[Solution, float | TupleFitness][source]
get_n_best_solution(n_solutions: int) → List[Tuple[Solution, float | TupleFitness]][source]
get_random_best_solution() → Tuple[Solution, float | TupleFitness][source]
get_random_solution() → Tuple[Solution, float | TupleFitness][source]
list_solution_fits: List[Tuple[Solution, float | TupleFitness]]
map_solutions: Dict[Solution, float | TupleFitness]
remove_duplicate_solutions(var_name: str) → None[source]
discrete_optimization.generic_tools.result_storage.result_storage.from_solutions_to_result_storage(list_solution: List[Solution], problem: Problem, params_objective_function: ParamsObjectiveFunction | None = None) → ResultStorage[source]
discrete_optimization.generic_tools.result_storage.result_storage.merge_results_storage(result_1: ResultStorage, result_2: ResultStorage) → ResultStorage[source]
discrete_optimization.generic_tools.result_storage.result_storage.plot_fitness(result_storage: ResultStorage, ax: Any | None = None, color: str = 'b', title: str = '') → Any[source]
discrete_optimization.generic_tools.result_storage.result_storage.plot_pareto_2d(pareto_front: ParetoFront, name_axis: List[str], ax: Any | None = None, color: str = 'b') → Any[source]
discrete_optimization.generic_tools.result_storage.result_storage.plot_storage_2d(result_storage: ResultStorage, name_axis: List[str], ax: Any | None = None, color: str = 'r') → None[source]
discrete_optimization.generic_tools.result_storage.result_storage.result_storage_to_pareto_front(result_storage: ResultStorage, problem: Problem | None = None) → ParetoFront[source]

discrete_optimization.generic_tools.result_storage.resultcomparator module

class discrete_optimization.generic_tools.result_storage.resultcomparator.ResultComparator(list_result_storage: List[ResultStorage], result_storage_names: List[str], objectives_str: List[str], objective_weights: List[int], test_problems: List[Problem] | None = None)[source]

Bases: object

generate_super_pareto() → ParetoFront[source]
get_best_by_objective_by_result_storage(objectif_str: str) → Dict[str, Tuple[Solution, float | TupleFitness]][source]
plot_all_2d_paretos_single_plot(objectives_str: List[str] | None = None) → Axes[source]
plot_all_2d_paretos_subplots(objectives_str: List[str] | None = None) → Figure[source]
plot_all_best_by_objective(objectif_str: str) → None[source]
plot_distribution_for_objective(objective_str: str) → Figure[source]
plot_super_pareto() → None[source]
print_test_distribution() → None[source]
reevaluate_result_storages() → None[source]

Module contents