class_docstr: Base class for evaluating methods for optimisation. 
class_docstr_tok: ["Base","class","for","evaluating","methods","for","optimisation","."]
docstr: Constructor. Also see BasicExperimenter for more args. 
docstr_tok: ["Constructor",".","Also","see","BasicExperimenter","for","more","args","."]
code: def __init__(
      self,
      study_name,
      func_caller,
      worker_manager,
      max_capital,
      methods,
      num_trials,
      save_dir,
      evaluation_options,
      save_file_prefix="",
      method_options=None,
      reporter=None,
      **kwargs,
  ):
      """Constructor. Also see BasicExperimenter for more args."""
      # pylint: disable=too-many-arguments
      self.func_caller = func_caller
      save_file_name = self._get_save_file_name(
          save_dir,
          study_name,
          worker_manager.num_workers,
          save_file_prefix,
          worker_manager.get_time_distro_info(),
          max_capital,
      )
      super(OptMethodEvaluator, self).__init__(
          study_name,
          num_trials,
          save_file_name,
          reporter=reporter,
          **kwargs,
      )
      self.worker_manager = worker_manager
      self.max_capital = float(max_capital)
      # Methods
      self.methods = methods
      self.num_methods = len(methods)
      self.domain = func_caller.domain
      self.method_options = (
          method_options
          if method_options
          else {key: None for key in methods}
      )
      # Experiment options will have things such as if the evaluations are noisy,
      # the time distributions etc.
      self.evaluation_options = evaluation_options
      self._set_up_saving()
  
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 1 to create a new OptMethodEvaluator object from inherited base classes: BaseMethodEvaluator with example: obj = OptMethodEvaluator(study_name, func_caller, worker_manager, max_capital, methods, num_trials, save_dir, evaluation_options, save_file_prefix, method_options, reporter)