class_docstr: Blackbox Optimiser Class. 
class_docstr_tok: ["Blackbox","Optimiser","Class","."]
docstr: Helper function for generating qinfos
docstr_tok: ["Helper","function","for","generating","qinfos"]
code: def _generate_qinfos(self, points):
      """Helper function for generating qinfos"""
      qinfos = []
      if self.is_an_mf_method():
          for point in points:
              if self.domain.get_type() == "euclidean":
                  (
                      z,
                      x,
                  ) = self.func_caller.get_normalised_fidel_domain_coords(
                      point[0], point[1]
                  )
              else:
                  z, x = self.func_caller.get_processed_fidel_from_raw(
                      point[0]
                  ), self.func_caller.get_processed_domain_point_from_raw(
                      point[1]
                  )
              qinfos.append(
                  Namespace(
                      point=x, val=point[2], true_val=point[2], fidel=z
                  )
              )
      else:
          for point in points:
              if self.domain.get_type() == "euclidean":
                  x = self.func_caller.get_normalised_domain_coords(
                      point[0]
                  )
              else:
                  x = self.func_caller.get_processed_domain_point_from_raw(
                      point[0]
                  )
              qinfos.append(
                  Namespace(point=x, val=point[1], true_val=point[1])
              )
      return qinfos
  
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 22 for calling the BlackboxOptimiser obj's underlying member method code with example usage: obj._generate_qinfos(points) and returns: qinfos