class_docstr: Base class for aggregation functions.
class_docstr_tok: ["Base","class","for","aggregation","functions","."]
docstr: Aggregate grouped pair of values.
  
  :param pair: The grouped pair of values.
  :type pair: tuple
  :returns: The aggregated values.
  :rtype: numpy.ndarray
docstr_tok: ["Aggregate","grouped","pair","of","values",".",":","param","pair",":","The","grouped","pair","of","values",".",":","type","pair",":","tuple",":","returns",":","The","aggregated","values",".",":","rtype",":","numpy.ndarray"]
code: def _agg_func_grouped(self, pair):
      """Aggregate grouped pair of values.
  
      :param pair: The grouped pair of values.
      :type pair: tuple
      :returns: The aggregated values.
      :rtype: numpy.ndarray
      """
      pass
  
imports: import logging
  import math
  import warnings
  from abc import ABC, abstractmethod
  import numpy
  import pandas
  from sklearn.metrics import multilabel_confusion_matrix
  from erroranalysis._internal.cohort_filter import filter_from_cohort
  from erroranalysis._internal.constants import DIFF, PRED_Y, ROW_INDEX, TRUE_Y, MatrixParams, MetricKeys, Metrics, ModelTask, metric_to_display_name
  from erroranalysis._internal.metrics import get_ordered_classes, is_multi_agg_metric, metric_to_func
  from raiutils.exceptions import UserConfigValidationException
label_desc: Use image node_id 3 for calling the _BaseAggFunc obj's underlying member method code with example usage: obj._agg_func_grouped(pair) without return types