code: def _ttei(gp_eval, anc_data, ref_point):
      """Computes the arm that is expected to do best over ref_point."""
      ref_mean, ref_std = gp_eval([ref_point])
      ref_mean = float(ref_mean)
      ref_std = float(ref_std)
  
      def _tt_ei_acq(x):
          """Acquisition for TTEI."""
          mu, sigma = gp_eval(x)
          comb_std = np.sqrt(ref_std**2 + sigma**2)
          norm_diff = (mu - ref_mean) / comb_std
          return comb_std * _expected_improvement_for_norm_diff(
              norm_diff
          )
  
      return maximise_acquisition(_tt_ei_acq, anc_data)
  
imports: from __future__ import division
  from argparse import Namespace
  from copy import copy
  import numpy
  from scipy.stats import norm
  from ..utils.general_utils import solve_lower_triangular
  from ..gp.gp_core import get_post_covar_from_raw_covar
  from ..exd.domains import EuclideanDomain
  from ..exd.exd_utils import maximise_with_method
label_desc: Use image node_id 20 for calling a global function with example usage: _ttei(gp_eval, anc_data, ref_point) and returns: maximise_acquisition, unknown