test_multi_objective.py

from typing import Tuple

from optuna import create_study
from optuna.study._multi_objective import _get_pareto_front_trials_2d
from optuna.study._multi_objective import _get_pareto_front_trials_nd
from optuna.trial import FrozenTrial


def _trial_to_values(t: FrozenTrial) -> Tuple[float, ...]:
    assert t.values is not None
    return tuple(t.values)


def test_get_pareto_front_trials_2d() -> None:
    study = create_study(directions=["minimize", "maximize"])
    assert {_trial_to_values(t) for t in _get_pareto_front_trials_2d(study)} == set()

    study.optimize(lambda t: [2, 2], n_trials=1)
    assert {_trial_to_values(t) for t in _get_pareto_front_trials_2d(study)} == {(2, 2)}

    study.optimize(lambda t: [1, 1], n_trials=1)
    assert {_trial_to_values(t) for t in _get_pareto_front_trials_2d(study)} == {(1, 1), (2, 2)}

    study.optimize(lambda t: [3, 1], n_trials=1)
    assert {_trial_to_values(t) for t in _get_pareto_front_trials_2d(study)} == {(1, 1), (2, 2)}

    study.optimize(lambda t: [3, 2], n_trials=1)
    assert {_trial_to_values(t) for t in _get_pareto_front_trials_2d(study)} == {(1, 1), (2, 2)}

    study.optimize(lambda t: [1, 3], n_trials=1)
    assert {_trial_to_values(t) for t in _get_pareto_front_trials_2d(study)} == {(1, 3)}
    assert len(_get_pareto_front_trials_2d(study)) == 1

    study.optimize(lambda t: [1, 3], n_trials=1)  # The trial result is the same as the above one.
    assert {_trial_to_values(t) for t in _get_pareto_front_trials_2d(study)} == {(1, 3)}
    assert len(_get_pareto_front_trials_2d(study)) == 2


def test_get_pareto_front_trials_nd() -> None:
    study = create_study(directions=["minimize", "maximize", "minimize"])
    assert {_trial_to_values(t) for t in _get_pareto_front_trials_nd(study)} == set()

    study.optimize(lambda t: [2, 2, 2], n_trials=1)
    assert {_trial_to_values(t) for t in _get_pareto_front_trials_nd(study)} == {(2, 2, 2)}

    study.optimize(lambda t: [1, 1, 1], n_trials=1)
    assert {_trial_to_values(t) for t in _get_pareto_front_trials_nd(study)} == {
        (1, 1, 1),
        (2, 2, 2),
    }

    study.optimize(lambda t: [3, 1, 3], n_trials=1)
    assert {_trial_to_values(t) for t in _get_pareto_front_trials_nd(study)} == {
        (1, 1, 1),
        (2, 2, 2),
    }

    study.optimize(lambda t: [3, 2, 3], n_trials=1)
    assert {_trial_to_values(t) for t in _get_pareto_front_trials_nd(study)} == {
        (1, 1, 1),
        (2, 2, 2),
    }

    study.optimize(lambda t: [1, 3, 1], n_trials=1)
    assert {_trial_to_values(t) for t in _get_pareto_front_trials_nd(study)} == {(1, 3, 1)}
    assert len(_get_pareto_front_trials_nd(study)) == 1

    study.optimize(
        lambda t: [1, 3, 1], n_trials=1
    )  # The trial result is the same as the above one.
    assert {_trial_to_values(t) for t in _get_pareto_front_trials_nd(study)} == {(1, 3, 1)}
    assert len(_get_pareto_front_trials_nd(study)) == 2