code: def eval(self):
      data_file = open(self.file_name, "r")
      line = data_file.readline()
  
      while line:
          # Get data
          if line.find("CATS-online") != -1:
              self.costs.append(
                  LossStructOn(
                      "cats", 0, 0, sys.float_info.max, 0, 0, 0, 0, 0
                  )
              )
          elif line.find("Discretized-Tree-online") != -1:
              self.costs.append(
                  LossStructOn(
                      "disc_tree",
                      0,
                      0,
                      sys.float_info.max,
                      0,
                      0,
                      0,
                      0,
                      0,
                  )
              )
          elif line.find("Discretized-Linear-online") != -1:
              self.costs.append(
                  LossStructOn(
                      "disc_linear",
                      0,
                      0,
                      sys.float_info.max,
                      0,
                      0,
                      0,
                      0,
                      0,
                  )
              )
  
          elif line.find("timeout") != -1:
              s1 = line.split()
              self.max_time = float(nextword("timeout", s1))
  
          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("Max Cost=") != -1:
              separator_position = len("Max Cost=")
              self.costs[len(self.costs) - 1].max_cost = float(
                  line[separator_position:]
              )
  
          elif line.find("number of examples") != -1:
              s1 = line.split()
              self.costs[len(self.costs) - 1].nb_examples = int(
                  nextword("=", s1)
              )
  
          elif line.find("average loss") != -1:
              s1 = line.split()
              self.costs[len(self.costs) - 1].loss = float(
                  nextword("=", s1)
              )
  
          elif line.find("real") != -1:
              s1 = line.split()
              self.costs[len(self.costs) - 1].time = float(
                  nextword("real", s1)
              )
  
          line = data_file.readline()
  
      self.get_best_loss()
  
      self.saveConfidenceIntervals(self.best_cats)
      self.saveConfidenceIntervals(self.best_disc_tree)
      self.saveConfidenceIntervals(self.best_disc_linear)
  
      if not self.quiet:
          self.printAllResults()
  
          print("max_time = ", self.max_time)
  
          self.printBestResults(self.best_cats)
          self.printBestResults(self.best_disc_tree)
          self.printBestResults(self.best_disc_linear)
  
      self.find_error()
  
file_path: vowpal_wabbit/demo/cats/utility/get_online_results.py
imports: import sys
  import getopt
  from confidence_interval import ConfidenceInterval
label_desc: Use image node_id 2 for calling the EvaluatorOnline obj's underlying member method code with example usage: obj.eval() without return types