from typing import NamedTuple
from typing import Optional
from typing import Sequence
from typing import Tuple
from typing import Union
import warnings
import optuna
from optuna.exceptions import ExperimentalWarning
from optuna.study import Study
from optuna.study._multi_objective import _get_pareto_front_trials_by_trials
from optuna.trial import FrozenTrial
from optuna.trial import TrialState
from optuna.visualization._plotly_imports import _imports
if _imports.is_successful():
from optuna.visualization._plotly_imports import go
_logger = optuna.logging.get_logger(__name__)
class _ParetoFrontInfo(NamedTuple):
n_targets: int
target_names: List[str]
best_trials_with_values: List[Tuple[FrozenTrial, List[float]]]
non_best_trials_with_values: List[Tuple[FrozenTrial, List[float]]]
infeasible_trials_with_values: List[Tuple[FrozenTrial, List[float]]]
axis_order: List[int]
include_dominated_trials: bool
has_constraints_func: bool
import pytest
import optuna
from optuna import Study
from optuna.study import create_study
from optuna.testing.visualization import prepare_study_with_trials
from optuna.trial import create_trial
from optuna.visualization import plot_edf as plotly_plot_edf
from optuna.visualization._edf import _EDFInfo
from optuna.visualization._edf import _get_edf_info
from optuna.visualization._edf import NUM_SAMPLES_X_AXIS
from optuna.visualization._plotly_imports import _imports as plotly_imports
from optuna.visualization.matplotlib import plot_edf as plt_plot_edf
from optuna.visualization.matplotlib._matplotlib_imports import _imports as plt_imports
if plotly_imports.is_successful():
from optuna.visualization._plotly_imports import go
if plt_imports.is_successful():
from optuna.visualization.matplotlib._matplotlib_imports import Axes
from optuna.visualization.matplotlib._matplotlib_imports import plt
parametrized_plot_edf = pytest.mark.parametrize(
"plot_edf", [plotly_plot_edf, plt_plot_edf])
def save_static_image(figure: Union[go.Figure, Axes, np.ndarray]) -> None:
if isinstance(figure, go.Figure):
figure.write_image(BytesIO())
else:
plt.savefig(BytesIO())
