class_docstr: Blackbox Optimiser Class. 
class_docstr_tok: ["Blackbox","Optimiser","Class","."]
docstr: Updates to the history specific to optimisation. 
docstr_tok: ["Updates","to","the","history","specific","to","optimisation","."]
code: def _exd_child_update_history(self, qinfo):
      """Updates to the history specific to optimisation."""
      # Update the best point/val
      # check fidelity
      if self.multi_func_caller.is_mf():
          raise NotImplementedError(_NO_MF_FOR_MOO_ERR_MSG)
      else:
          self._update_opt_point_and_val(qinfo)
      # Now add to history
      self.history.curr_pareto_vals.append(self.curr_pareto_vals)
      self.history.curr_pareto_points.append(self.curr_pareto_points)
      self.history.curr_true_pareto_vals.append(
          self.curr_true_pareto_vals
      )
      self.history.curr_true_pareto_points.append(
          self.curr_true_pareto_points
      )
      # Any method specific updating
      self._multi_opt_method_update_history(qinfo)
  
imports: from __future__ import division
  from argparse import Namespace
  import numpy
  from ..exd.exd_core import ExperimentDesigner, exd_core_args
  from ..exd.experiment_caller import MultiFunctionCaller, FunctionCaller
  from ..exd.exd_utils import EVAL_ERROR_CODE
  from ..utils.general_utils import update_pareto_set
label_desc: Use image node_id 6 for calling the MultiObjectiveOptimiser obj's underlying member method code with example usage: obj._exd_child_update_history(qinfo) without return types