class_docstr: Blackbox Optimiser Class. 
class_docstr_tok: ["Blackbox","Optimiser","Class","."]
docstr: Set up for black-box optimisation. 
docstr_tok: ["Set","up","for","black-box","optimisation","."]
code: def _blackbox_optimise_set_up(self):
      """Set up for black-box optimisation."""
      # Initialise optimal value and point
      self.curr_opt_val = -np.inf
      self.curr_opt_point = None
      self.curr_true_opt_val = -np.inf
      self.curr_true_opt_point = None
      # Set up history
      self.history.query_vals = []
      self.history.query_true_vals = []
      self.history.curr_opt_vals = []
      self.history.curr_opt_points = []
      self.history.curr_true_opt_vals = []
      self.history.curr_true_opt_points = []
      if self.func_caller.is_mf():
          self.history.query_at_fidel_to_opts = []
      # Set up attributes to be copied from history
      self.to_copy_from_qinfo_to_history["val"] = "query_vals"
      self.to_copy_from_qinfo_to_history["true_val"] = "query_true_vals"
      # Set up previous evaluations
      self.prev_eval_vals = []
      self.prev_eval_true_vals = []
      self.history.prev_eval_vals = self.prev_eval_vals
      self.history.prev_eval_true_vals = self.prev_eval_true_vals
  
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 3 for calling the BlackboxOptimiser obj's underlying member method code with example usage: obj._blackbox_optimise_set_up() without return types