class_docstr: Blackbox Optimiser Class. 
class_docstr_tok: ["Blackbox","Optimiser","Class","."]
docstr: Updates the optimum point and value according the data in qinfo.
  Can be overridden by a child class if you want to do anything differently.
docstr_tok: ["Updates","the","optimum","point","and","value","according","the","data","in","qinfo",".","Can","be","overridden","by","a","child","class","if","you","want","to","do","anything","differently","."]
code: def _update_opt_point_and_val(
      self, qinfo, query_is_at_fidel_to_opt=None
  ):
      """Updates the optimum point and value according the data in qinfo.
      Can be overridden by a child class if you want to do anything differently.
      """
      if query_is_at_fidel_to_opt is not None:
          if not query_is_at_fidel_to_opt:
              # if the fidelity queried at is not fidel_to_opt, then return
              return
      if qinfo.val == EVAL_ERROR_CODE:
          return
      # Optimise curr_opt_val and curr_true_opt_val
      (
          self.curr_pareto_vals,
          self.curr_pareto_points,
      ) = update_pareto_set(
          self.curr_pareto_vals,
          self.curr_pareto_points,
          qinfo.val,
          qinfo.point,
      )
      (
          self.curr_true_pareto_vals,
          self.curr_true_pareto_points,
      ) = update_pareto_set(
          self.curr_true_pareto_vals,
          self.curr_true_pareto_points,
          qinfo.true_val,
          qinfo.point,
      )
  
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 7 for calling the MultiObjectiveOptimiser obj's underlying member method code with example usage: obj._update_opt_point_and_val(qinfo, query_is_at_fidel_to_opt) without return types