コード例 #1
0
from typing import Callable
from typing import Optional

from optuna._experimental import experimental
from optuna.logging import get_logger
from optuna.study import Study
from optuna.study import StudyDirection
from optuna.trial import FrozenTrial
from optuna.trial import TrialState
from optuna.visualization.matplotlib._matplotlib_imports import _imports

if _imports.is_successful():
    from optuna.visualization.matplotlib._matplotlib_imports import Axes
    from optuna.visualization.matplotlib._matplotlib_imports import plt

_logger = get_logger(__name__)


@experimental("2.2.0")
def plot_optimization_history(
    study: Study,
    *,
    target: Optional[Callable[[FrozenTrial], float]] = None,
    target_name: str = "Objective Value",
) -> "Axes":
    """Plot optimization history of all trials in a study with Matplotlib.

    .. seealso::
        Please refer to :func:`optuna.visualization.plot_optimization_history` for an example.

    Example:
コード例 #2
0
ファイル: test_edf.py プロジェクト: HideakiImamura/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())


@parametrized_plot_edf