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"""
plot_pareto_front
=================
.. autofunction:: optuna.visualization.plot_pareto_front
The following code snippet shows how to plot the Pareto front of a study.
"""
import optuna
from plotly.io import show
def objective(trial):
x = trial.suggest_float("x", 0, 5)
y = trial.suggest_float("y", 0, 3)
v0 = 4 * x**2 + 4 * y**2
v1 = (x - 5) ** 2 + (y - 5) ** 2
return v0, v1
study = optuna.create_study(directions=["minimize", "minimize"])
study.optimize(objective, n_trials=50)
fig = optuna.visualization.plot_pareto_front(study)
show(fig)
# %%
# The following code snippet shows how to plot a 2-dimensional Pareto front
# of a 3-dimensional study.
# This example is scalable, e.g., for plotting a 2- or 3-dimensional Pareto front
# of a 4-dimensional study and so on.
import optuna
from plotly.io import show
def objective(trial):
x = trial.suggest_float("x", 0, 5)
y = trial.suggest_float("y", 0, 3)
v0 = 5 * x**2 + 3 * y**2
v1 = (x - 10) ** 2 + (y - 10) ** 2
v2 = x + y
return v0, v1, v2
study = optuna.create_study(directions=["minimize", "minimize", "minimize"])
study.optimize(objective, n_trials=100)
fig = optuna.visualization.plot_pareto_front(
study,
targets=lambda t: (t.values[0], t.values[1]),
target_names=["Objective 0", "Objective 1"],
)
show(fig)
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