code: def test_aggregate_individual_image_results(self):
      curve_x = [0.0, 0.25, 0.5, 0.75, 1.0]
      metric_result_1 = pic.PicMetricResult(
          curve_x=curve_x,
          curve_y=[0.0, 0.2, 0.4, 0.6, 1.0],
          blurred_images=[],
          predictions=[],
          thresholds=[],
          auc=0.4,
      )
      metric_result_2 = pic.PicMetricResult(
          curve_x=curve_x,
          curve_y=[0.0, 0.4, 0.4, 0.4, 1.0],
          blurred_images=[],
          predictions=[],
          thresholds=[],
          auc=0.2,
      )
  
      r = pic.aggregate_individual_pic_results(
          [metric_result_1, metric_result_2], method="mean"
      )
      self.assertEqual(len(r.curve_x), len(curve_x))
      self.assertEqual(len(r.curve_y), len(curve_x))
      np.testing.assert_almost_equal(
          r.curve_x, [0.0, 0.25, 0.5, 0.75, 1.0]
      )
      np.testing.assert_almost_equal(
          r.curve_y, [0.0, 0.3, 0.4, 0.5, 1.0]
      )
      self.assertEqual(
          r.auc,
          (0 + 0.3) / 8
          + (0.3 + 0.4) / 8
          + (0.4 + 0.5) / 8
          + (0.5 + 1.0) / 8,
      )
      self.assertGreater(r.auc, 0.0)
      self.assertLess(r.auc, 1.0)
  
file_path: saliency/saliency/metrics/pic_test.py
imports: import numpy
  import os
  import unittest
  from .None import pic
  from pathlib import Path
  from PIL import Image
label_desc: Use image node_id 9 for calling the PicTest obj's underlying member method code with example usage: obj.test_aggregate_individual_image_results() without return types