code: def eval(self):
      data_file = open(self.srm_file_name, "r")
      line = data_file.readline()
  
      count = 0
      while line:
          # Get data
          if line.find("CATS-offline") != -1:
              self.costs.append(
                  LossStructOff(0, 0, 0, 0, 0, 0, 0, 0, 0)
              )
              count += 1
          elif line.find("n = ") != -1:
              separator_position = len("n = ")
              separator_position_end = line.find("\n")
              self.costs[len(self.costs) - 1].n = float(
                  line[separator_position:separator_position_end]
              )
  
          elif line.find("h = ") != -1:
              separator_position = len("h = ")
              separator_position_end = line.find("\n")
              self.costs[len(self.costs) - 1].h = float(
                  line[separator_position:separator_position_end]
              )
  
          elif line.find("srm") != -1:
              s1 = line.split()
              self.costs[len(self.costs) - 1].srm = float(
                  nextword("=", s1)
              )
  
          line = data_file.readline()
  
      data_file = open(self.test_file_name, "r")
      line = data_file.readline()
  
      count = 0
      while line:
          # Get data
          if line.find("CATS-offline") != -1:
              count += 1
  
          elif line.find("n = ") != -1:
              separator_position = len("n = ")
              separator_position_end = line.find("\n")
              if self.costs[count - 1].n != float(
                  line[separator_position:separator_position_end]
              ):
                  print("error: n is not matched")
  
          elif line.find("h = ") != -1:
              separator_position = len("h = ")
              separator_position_end = line.find("\n")
              if self.costs[count - 1].h != float(
                  line[separator_position:separator_position_end]
              ):
                  print("error: h is not matched")
  
          elif line.find("test_loss") != -1:
              s1 = line.split()
              self.costs[count - 1].test_loss = float(nextword("=", s1))
  
          elif line.find("max_loss") != -1:
              s1 = line.split()
              self.costs[count - 1].max_loss = float(nextword("=", s1))
  
          elif line.find("nb_examples") != -1:
              s1 = line.split()
              self.costs[count - 1].nb_examples = float(
                  nextword("=", s1)
              )
  
          line = data_file.readline()
  
      self.calc_srm_penalty()
      self.get_optimized()
  
      self.saveConfidenceIntervals(self.initial)
      self.saveConfidenceIntervals(self.optimized)
  
      if not self.quiet:
          self.printAllResults()
          print("\ninitial model:")
          self.printResults(self.initial)
          print("optimized model:")
          self.printResults(self.optimized)
  
file_path: vowpal_wabbit/demo/cats/utility/get_offline_results.py
imports: import sys
  import getopt
  import math
  from confidence_interval import ConfidenceInterval
label_desc: Use image node_id 2 for calling the EvaluatorOffline obj's underlying member method code with example usage: obj.eval() without return types