code: def test_metric_is_not_1_for_incorrect(metric, expected_value):
      """Tests if correct MAP values are computed
      Load ground truth and dict for incorrect map prediction to have a Map less than 1.0
      """
      ground_truth, retrieved = return_ground_incorrect_retrievals()
      metric_val = mean_metric(ground_truth, retrieved, metric=metric)
      assert metric_val == expected_value
  
file_path: imagededup/tests/test_information_retrieval.py
imports: import pickle
  import pytest
  from pathlib import Path
  from imagededup.handlers.metrics.information_retrieval import *
label_desc: Use image node_id 13 for calling a global function with example usage: test_metric_is_not_1_for_incorrect(metric, expected_value) without return types