Fcmaes
Abstract C++ optimized implementation of CMA-ES using the fcmaes library (https://github.com/dietmarwo/fast-cma-es). To use this package, please install the fcmaes library.
APIs FastCmaesSampler
Example from __future__ import annotations import numpy as np import optuna import optunahub def SphereIntCOM(x: np.ndarray, z: np.ndarray, c: np.ndarray) -> float: return sum(x * x) + sum(z * z) + len(c) - sum(c[:, 0]) def objective(trial: optuna.Trial) -> float: x1 = trial.suggest_float("x1", -5, 5) x2 = trial.suggest_float("x2", -5, 5) z1 = trial.