optuna.visualization.matplotlib.plot_optimization_history

optuna.visualization.matplotlib.plot_optimization_history(study: optuna.study.Study) → matplotlib.axes._axes.Axes

Plot optimization history of all trials in a study with Matplotlib.

See also

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

Example

The following code snippet shows how to plot optimization history.

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_optimization_history(study)

Parameters

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

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.