class_docstr: Base class for evaluating methods for optimisation. 
class_docstr_tok: ["Base","class","for","evaluating","methods","for","optimisation","."]
docstr: Returns an empty array to be used for saving results of current iteration. 
docstr_tok: ["Returns","an","empty","array","to","be","used","for","saving","results","of","current","iteration","."]
code: def _get_new_iter_results_array(self):
      """Returns an empty array to be used for saving results of current iteration."""
      #     return np.empty((self.num_methods, 1), dtype=np.object)
      return np.array(
          [["-"] for _ in range(self.num_methods)], dtype=np.object
      )
  
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 5 for calling the OptMethodEvaluator obj's underlying member method code with example usage: obj._get_new_iter_results_array() and returns: np