code: def test_labels_to_ranges(test_case: Dict):
      expected_ranges_ls = test_case["ranges"]
      obtained_ranges_ls = labels_to_ranges(test_case["labels"])
      assert expected_ranges_ls == obtained_ranges_ls, (
          "Obtained list of ranges do not match the expected list. "
          f"Expected: f{expected_ranges_ls}, obtained: f{obtained_ranges_ls}"
      )
  
file_path: gluonts/test/nursery/anomaly_detection/supervised_metrics/test_precision_recall.py
imports: from typing import Dict, List, Tuple
  import numpy
  import pytest
  from sklearn.metrics import auc
  from gluonts.nursery.anomaly_detection.supervised_metrics import aggregate_precision_recall_curve, buffered_precision_recall, segment_precision_recall
  from gluonts.nursery.anomaly_detection.supervised_metrics._buffered_precision_recall import extend_ranges
  from gluonts.nursery.anomaly_detection.supervised_metrics.bounded_pr_auc import bounded_pr_auc
  from gluonts.nursery.anomaly_detection.supervised_metrics.utils import labels_to_ranges, range_overlap
label_desc: Use image node_id 2 for calling a global function with example usage: test_labels_to_ranges(test_case) without return types