plot_intermediate_values

optuna.visualization.matplotlib.plot_intermediate_values(study)

Plot intermediate values of all trials in a study with Matplotlib.

See also

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

Note

Please refer to matplotlib.pyplot.legend to adjust the style of the generated legend.

Parameters:

study (Study) – A Study object whose trials are plotted for their intermediate values.

Returns:

A matplotlib.axes.Axes object.

Return type:

Axes

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.

The following code snippet shows how to plot intermediate values.

/home/docs/checkouts/readthedocs.org/user_builds/optuna/checkouts/stable/docs/visualization_matplotlib_examples/optuna.visualization.matplotlib.intermediate_values.py:44: ExperimentalWarning:

plot_intermediate_values is experimental (supported from v2.2.0). The interface can change in the future.


<Axes: title={'center': 'Intermediate Values Plot'}, xlabel='Step', ylabel='Intermediate Value'>

import optuna


def f(x):
    return (x - 2) ** 2


def df(x):
    return 2 * x - 4


def objective(trial):
    lr = trial.suggest_float("lr", 1e-5, 1e-1, log=True)

    x = 3
    for step in range(128):
        y = f(x)

        trial.report(y, step=step)
        if trial.should_prune():
            raise optuna.TrialPruned()

        gy = df(x)
        x -= gy * lr

    return y


sampler = optuna.samplers.TPESampler(seed=10)
study = optuna.create_study(sampler=sampler)
study.optimize(objective, n_trials=16)

optuna.visualization.matplotlib.plot_intermediate_values(study)