dd066d40d87fd081598adbec2676371a595be25b,optuna/multi_objective/_hypervolume/wfg.py,WFG,_limit,#Any#Any#,57

Before Change

            if (solution_set[i] <= point).all():
                return point.reshape((1, dim))
            limited_solution_set.append(np.maximum(solution_set[i], point))
        limited_solution_set = np.asarray(limited_solution_set).reshape(
            (len(limited_solution_set), dim)
        )

        // Return only Pareto optimal points for computational efficiency.
        if n_points_of_s <= 1:
            return limited_solution_set

After Change

        
        n_points_of_s = solution_set.shape[0]

        limited_solution_set = np.maximum(solution_set, point)

        // Return only Pareto optimal points for computational efficiency.
        if n_points_of_s <= 1:
            return limited_solution_set

Instances