code: def test_tradeoff_curve():
      for sensitive_feature_value in sensitive_feature_names_ex1:
          (
              grouped_data,
              base_points,
              ignore_for_base_points,
              x_grid,
          ) = _get_grouped_data_and_base_points(sensitive_feature_value)
  
          roc_convex_hull = _tradeoff_curve(
              grouped_data, x_grid, sensitive_feature_value
          )
          curve = _interpolate_curve(
              roc_convex_hull, "x", "y", "operation", x_grid
          )
  
          _assert_interpolated_points_are_between_base_points(
              base_points, curve, ignore_for_base_points
          )
  
file_path: fairlearn/test/unit/postprocessing/test_curve_utilities.py
imports: import numpy
  import pandas
  import pytest
  from fairlearn.postprocessing._constants import LABEL_KEY, SCORE_KEY, SENSITIVE_FEATURE_KEY
  from fairlearn.postprocessing._threshold_operation import ThresholdOperation
  from fairlearn.postprocessing._tradeoff_curve_utilities import _calculate_tradeoff_points, _filter_points_to_get_convex_hull, _interpolate_curve, _tradeoff_curve
  from .conftest import _get_grouped_data_and_base_points, labels_ex, scores_ex, sensitive_feature_names_ex1, sensitive_features_ex1
label_desc: Use image node_id 5 for calling a global function with example usage: test_tradeoff_curve() without return types