code: def test_get_summary_parameters(self, issue_manager, monkeypatch):
      mock_health_summary_parameters = {
          "labels": [1, 0, 2],
          "asymmetric": False,
          "class_names": ["a", "b", "c"],
          "num_examples": 3,
          "joint": [1 / 3, 1 / 3, 1 / 3],
          "confident_joint": [1 / 3, 1 / 3, 1 / 3],
          "multi_label": False,
      }
      pred_probs = np.random.rand(3, 3)
      monkeypatch.setattr(
          issue_manager,
          "health_summary_parameters",
          mock_health_summary_parameters,
      )
      summary_parameters = issue_manager._get_summary_parameters(
          pred_probs=pred_probs
      )
      expected_parameters = {
          "confident_joint": [1 / 3, 1 / 3, 1 / 3],
          "asymmetric": False,
          "class_names": ["a", "b", "c"],
      }
      assert summary_parameters == expected_parameters
  
      # Test missing "confident_joint" key
      mock_health_summary_parameters.pop("confident_joint")
      monkeypatch.setattr(
          issue_manager,
          "health_summary_parameters",
          mock_health_summary_parameters,
      )
      summary_parameters = issue_manager._get_summary_parameters(
          pred_probs=pred_probs
      )
      expected_parameters = {
          "joint": [1 / 3, 1 / 3, 1 / 3],
          "num_examples": 3,
          "asymmetric": False,
          "class_names": ["a", "b", "c"],
      }
      assert summary_parameters == expected_parameters
  
      # Test missing "joint" key
      mock_health_summary_parameters.pop("joint")
      monkeypatch.setattr(
          issue_manager.datalab._labels,
          "labels",
          mock_health_summary_parameters["labels"],
      )
      monkeypatch.setattr(
          issue_manager,
          "health_summary_parameters",
          mock_health_summary_parameters,
      )
      summary_parameters = issue_manager._get_summary_parameters(
          pred_probs=pred_probs
      )
      expected_parameters = {
          "pred_probs": pred_probs,
          "labels": [1, 0, 2],
          "asymmetric": False,
          "class_names": ["a", "b", "c"],
      }
      assert np.all(
          summary_parameters["pred_probs"]
          == expected_parameters["pred_probs"]
      )
      summary_parameters.pop("pred_probs")
      expected_parameters.pop("pred_probs")
      assert summary_parameters == expected_parameters
  
file_path: cleanlab/tests/datalab/issue_manager/test_label.py
imports: import numpy
  import pandas
  import pytest
  from cleanlab.datalab.internal.issue_manager.label import LabelIssueManager
label_desc: Use image node_id 5 for calling the TestLabelIssueManager obj's underlying member method code with example usage: obj.test_get_summary_parameters(issue_manager, monkeypatch) without return types