code: def preprocess(self, data_group):
      # Relatively brittle, only works for 1-dimensional data.
      input_data = data_group.preprocessed_case
  
      # Probably not the most efficient.
      output_data = np.zeros(self.num_classes)
      for item in input_data:
          if self.class_dictionary != {}:
              output_data[self.class_dictionary[item]] = 1
          else:
              output_data[int(item)] = 1
  
      data_group.preprocessed_case = output_data
      self.output_data = output_data
  
imports: import subprocess
  import os
  import numpy
  import itertools
  from deepneuro.preprocessing.preprocessor import Preprocessor
  from deepneuro.utilities.util import add_parameter, quotes
label_desc: Use image node_id 3 for calling the OneHotEncode obj's underlying member method code with example usage: obj.preprocess(data_group) without return types