code: def test_interpolate_curve():
      # The operation is irrelevant in this case since its semantics are not
      # used within _interpolate_curve.
      base_points = pd.DataFrame(
          {
              "x": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
              "y": [-5, -2, -1.5, -1, 0, 0.5, 0.8, 1.0, 1.1, 1.15],
              "operation": [
                  "i",
                  "r",
                  "r",
                  "e",
                  "l",
                  "e",
                  "v",
                  "a",
                  "n",
                  "t",
              ],
          }
      )
      x_grid = np.linspace(0, 9, 100)
      curve = _interpolate_curve(
          base_points, "x", "y", "operation", x_grid
      )
  
      _assert_interpolated_points_are_between_base_points(
          base_points, curve
      )
  
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 2 for calling a global function with example usage: test_interpolate_curve() without return types