class_docstr: A class which optimises in Cartesian product spaces using random evaluations. 
class_docstr_tok: ["A","class","which","optimises","in","Cartesian","product","spaces","using","random","evaluations","."]
docstr: Returns initial qinfos. 
docstr_tok: ["Returns","initial","qinfos","."]
code: def _get_initial_qinfos(self, num_init_evals, *args, **kwargs):
      """Returns initial qinfos."""
      return get_cp_domain_initial_qinfos(
          self.domain,
          num_init_evals,
          self.fidel_space,
          self.func_caller.fidel_to_opt,
          set_to_fidel_to_opt_with_prob=self.call_fidel_to_opt_prob,
          dom_euclidean_sample_type="latin_hc",
          dom_integral_sample_type="latin_hc",
          dom_nn_sample_type="rand",
          fidel_space_euclidean_sample_type="latin_hc",
          fidel_space_integral_sample_type="latin_hc",
          fidel_space_nn_sample_type="rand",
          *args,
          **kwargs,
      )
  
imports: from argparse import Namespace
  import numpy
  from ..exd.cp_domain_utils import get_processed_func_from_raw_func_for_cp_domain, load_cp_domain_from_config_file
  from ..exd import domains
  from ..exd.exd_utils import get_euclidean_initial_qinfos, get_cp_domain_initial_qinfos
  from ..exd.exd_core import mf_exd_args
  from ..exd.experiment_caller import CPFunctionCaller
  from ..exd.cp_domain_utils import sample_from_cp_domain
  from ..exd.worker_manager import SyntheticWorkerManager
  from .blackbox_optimiser import BlackboxOptimiser, blackbox_opt_args, CalledMFOptimiserWithSFCaller
  from ..utils.option_handler import load_options
  from ..utils.reporters import get_reporter
  from ..utils.general_utils import map_to_bounds
label_desc: Use image node_id 5 for calling the MFCPRandomOptimiser obj's underlying member method code with example usage: obj._get_initial_qinfos(num_init_evals) and returns: get_cp_domain_initial_qinfos