code: def _extend_confusion_matrix(
      *,
      true_positives,
      false_positives,
      true_negatives,
      false_negatives,
  ):
      """Extend the provided confusion matrix counts with additional implied fields.
  
      Parameters
      ----------
      true_positives, false_positives, true_negatives, false_negatives : int
          The counts appearing in the confusion matrix.
  
      Returns
      -------
      result : sklearn.utils.Bunch
          Dictionary-like object, with attributes:
  
          true_positives, false_positives, true_negatives, false_negatives : int
              The provided counts.
  
          predicted_positives, predicted_negatives, positives, negatives, n : int
              Derived counts.
      """
      return Bunch(
          true_positives=true_positives,
          false_positives=false_positives,
          true_negatives=true_negatives,
          false_negatives=false_negatives,
          predicted_positives=(true_positives + false_positives),
          predicted_negatives=(true_negatives + false_negatives),
          positives=(true_positives + false_negatives),
          negatives=(true_negatives + false_positives),
          n=(
              true_positives
              + true_negatives
              + false_positives
              + false_negatives
          ),
      )
  
file_path: fairlearn/fairlearn/postprocessing/_tradeoff_curve_utilities.py
imports: import numpy
  import pandas
  from sklearn.utils import Bunch
  from ._constants import LABEL_KEY, P0_KEY, P1_KEY, SCORE_KEY
  from ._threshold_operation import ThresholdOperation
label_desc: Use image node_id 1 for calling a global function with example usage: _extend_confusion_matrix() and returns: Bunch