class_docstr: Base class for evaluating methods for optimisation. 
class_docstr_tok: ["Base","class","for","evaluating","methods","for","optimisation","."]
docstr: Gets the initial qinfos for all methods. 
docstr_tok: ["Gets","the","initial","qinfos","for","all","methods","."]
code: def _get_prev_eval_qinfos(self):
      """Gets the initial qinfos for all methods."""
      if self.evaluation_options.prev_eval_points.lower() == "generate":
          init_pool_qinfos = self._get_initial_pool_qinfos()
      elif self.evaluation_options.prev_eval_points.lower() == "none":
          return None
      else:
          # Load from the file.
          raise NotImplementedError(
              "Not written reading results from file yet."
          )
      # Create an initialiser
      initialiser = OptInitialiser(
          self.func_caller, self.worker_manager
      )
      initialiser.options.get_initial_qinfos = (
          lambda _: init_pool_qinfos
      )
      initialiser.options.max_num_steps = 0
      _, _, init_hist = initialiser.initialise()
      return init_hist.query_qinfos
  
imports: from argparse import Namespace
  from datetime import datetime
  import os
  import numpy
  from .blackbox_optimiser import OptInitialiser
  from ..utils.method_evaluator import BaseMethodEvaluator
label_desc: Use image node_id 9 for calling the OptMethodEvaluator obj's underlying member method code with example usage: obj._get_prev_eval_qinfos() and returns: init_hist, None