optuna.visualization.matplotlib.plot_slice

optuna.visualization.matplotlib.plot_slice(study: optuna.study.Study, params: Optional[List[str]] = None, *, target: Optional[Callable[[optuna.trial._frozen.FrozenTrial], float]] = None, target_name: str = 'Objective Value') → matplotlib.axes._axes.Axes

Plot the parameter relationship as slice plot in a study with Matplotlib.

See also

Please refer to optuna.visualization.plot_slice() for an example.

Example

The following code snippet shows how to plot the parameter relationship as slice plot.

import optuna


def objective(trial):
    x = trial.suggest_uniform("x", -100, 100)
    y = trial.suggest_categorical("y", [-1, 0, 1])
    return x ** 2 + y


sampler = optuna.samplers.TPESampler(seed=10)
study = optuna.create_study(sampler=sampler)
study.optimize(objective, n_trials=10)

optuna.visualization.matplotlib.plot_slice(study, params=["x", "y"])

Parameters

• study – A Study object whose trials are plotted for their target values.

• params – Parameter list to visualize. The default is all parameters.

• target – A function to specify the value to display. If it is None, the objective values are plotted.

• target_name – Target’s name to display on the axis label.

Returns

A matplotlib.axes.Axes object.

Note

Added in v2.2.0 as an experimental feature. The interface may change in newer versions without prior notice. See https://github.com/optuna/optuna/releases/tag/v2.2.0.