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.func_caller.is_mf():
          eval_fidel = (
              qinfo.fidel
              if hasattr(qinfo, "fidel")
              else self.func_caller.fidel_to_opt
          )
          query_is_at_fidel_to_opt = self.func_caller.is_fidel_to_opt(
              eval_fidel
          )
          self.history.query_at_fidel_to_opts.append(
              query_is_at_fidel_to_opt
          )
          self.num_fidel_to_opt_calls += query_is_at_fidel_to_opt
          self._update_opt_point_and_val(
              qinfo, query_is_at_fidel_to_opt
          )
      else:
          self._update_opt_point_and_val(qinfo)
      # Now add to history
      self.history.curr_opt_vals.append(self.curr_opt_val)
      self.history.curr_opt_points.append(self.curr_opt_point)
      self.history.curr_true_opt_vals.append(self.curr_true_opt_val)
      self.history.curr_true_opt_points.append(self.curr_true_opt_point)
      # Any method specific updating
      self._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 ..utils.option_handler import load_options
label_desc: Use image node_id 6 for calling the BlackboxOptimiser obj's underlying member method code with example usage: obj._exd_child_update_history(qinfo) without return types