code: def _compute_acq_withGradients(self, x):
          
          fmin = self.model.get_fmin()
          m, s, dmdx, dsdx = self.model.predict_withGradients(x)
          phi, Phi, u = get_quantiles(self.jitter, fmin, m, s)
          f_acqu = s * (u * Phi + phi)
          df_acqu = dsdx * phi - Phi * dmdx
          return f_acqu, df_acqu
docs: Computes the Expected Improvement and its derivative (has a very easy derivative!)