code: def get_quantiles(acquisition_par, fmin, m, s):
      '''
      Quantiles of the Gaussian distribution useful to determine the acquisition function values
      :param acquisition_par: parameter of the acquisition function
      :param fmin: current minimum.
      :param m: vector of means.
      :param s: vector of standard deviations.
      '''
      if isinstance(s, np.ndarray):
          s[s<1e-10] = 1e-10
      elif s< 1e-10:
          s = 1e-10
      u = (fmin - m - acquisition_par)/s
      phi = np.exp(-0.5 * u**2) / np.sqrt(2*np.pi)
      Phi = 0.5 * erfc(-u / np.sqrt(2))
      return (phi, Phi, uf get_quantiles(acquisition_par, fmin, m, s):
      '''
      Quantiles of the Gaussian distribution useful to determine the acquisition function values
      :param acquisition_par: parameter of the acquisition function
      :param fmin: current minimum.
      :param m: vector of means.
      :param s: vector of standard deviations.
      '''
      if isinstance(s, np.ndarray):
          s[s<1e-10] = 1e-10
      elif s< 1e-10:
          s = 1e-10
      u = (fmin - m - acquisition_par)/s
      phi = np.exp(-0.5 * u**2) / np.sqrt(2*np.pi)
      Phi = 0.5 * erfc(-u / np.sqrt(2))
      return (phi, Phi, u)
docs: Quantiles of the Gaussian distribution useful to determine the acquisition function values
      :param acquisition_par: parameter of the acquisition function
      :param fmin: current minimum.
      :param m: vector of means.
      :param s: vector of standard deviations.