class_docstr: Base class for evaluating methods for optimisation. 
class_docstr_tok: ["Base","class","for","evaluating","methods","for","optimisation","."]
docstr: Returns a new empty arrray to be used for saving results. 
docstr_tok: ["Returns","a","new","empty","arrray","to","be","used","for","saving","results","."]
code: def _get_new_empty_results_array(self):
      """Returns a new empty arrray to be used for saving results."""
      #     return np.empty((self.num_methods, 0), 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 4 for calling the OptMethodEvaluator obj's underlying member method code with example usage: obj._get_new_empty_results_array() and returns: np