nodes: 0, module; 1, function_definition; 2, function_name:classify_segmented_recording; 3, parameters; 4, block; 5, identifier:recording; 6, default_parameter; 7, expression_statement; 8, global_statement; 9, if_statement; 10, return_statement; 11, identifier:result_format; 12, None; 13, comment:"""Use this function if you are sure you have a single symbol.
  
      Parameters
      ----------
      recording : string
          The recording in JSON format
  
      Returns
      -------
      list of dictionaries
          Each dictionary contains the keys 'symbol' and 'probability'. The list
          is sorted descending by probability.
      """; 14, identifier:single_symbol_classifier; 15, comparison_operator:single_symbol_classifier is None; 16, block; 17, call; 18, identifier:single_symbol_classifier; 19, None; 20, expression_statement; 21, attribute; 22, argument_list; 23, assignment; 24, identifier:single_symbol_classifier; 25, identifier:predict; 26, identifier:recording; 27, identifier:result_format; 28, identifier:single_symbol_classifier; 29, call; 30, identifier:SingleClassificer; 31, argument_list
code: def classify_segmented_recording(recording, result_format=None):
      """Use this function if you are sure you have a single symbol.
  
      Parameters
      ----------
      recording : string
          The recording in JSON format
  
      Returns
      -------
      list of dictionaries
          Each dictionary contains the keys 'symbol' and 'probability'. The list
          is sorted descending by probability.
      """
      global single_symbol_classifier
      if single_symbol_classifier is None:
          single_symbol_classifier = SingleClassificer()
      return single_symbol_classifier.predict(recording, result_format)