b0699b34e2b16cb3abbd22c397077cc6c21ef279,skopt/optimizer/base.py,,base_minimize,#,29

Before Change

                with warnings.catch_warnings():
                    warnings.simplefilter("ignore")
                    x, a, _ = fmin_l_bfgs_b(
                        gaussian_acquisition_1D, x0,
                        args=(gp, np.min(yi), acq_func, xi, kappa),
                        bounds=space.transformed_bounds,

After Change

            cand_xs = np.array([r[0] for r in results])
            cand_acqs = np.array([r[1] for r in results])
            best_ind = np.argmin(cand_acqs)
            a = cand_acqs[best_ind]
            if a < best:
                next_x, best = cand_xs[best_ind], a

        // lbfg should handle this but just in case there are precision errors.
        next_x = np.clip(

Instances