docstr: Test some values in the info dict.
  
  Mainly focused on the clustering info.
docstr_tok: ["Test","some","values","in","the","info","dict",".","Mainly","focused","on","the","clustering","info","."]
code: def test_collect_info(self, issue_manager, make_data):
      """Test some values in the info dict.
  
      Mainly focused on the clustering info.
      """
      UNDERPERFORMING_CLUSTER_ID = 0
      data = make_data(noisy=True)
      features, pred_probs, labels = (
          data["features"],
          data["pred_probs"],
          data["labels"],
      )
      issue_manager.find_issues(
          features=features, pred_probs=pred_probs
      )
      info = issue_manager.info
      assert "weighted_knn_graph" in info["statistics"]
      assert "clustering" in info
      # Check clustering info
      clustering_info = info["clustering"]
      assert clustering_info["algorithm"] == "DBSCAN"
      assert clustering_info["params"]["metric"] == "precomputed"
      assert clustering_info["stats"]["n_clusters"] == 4
      # Test collect_info() with cluster_ids
      issue_manager.find_issues(
          features=features, pred_probs=pred_probs, cluster_ids=labels
      )
      info = issue_manager.info
      assert "nearest_neighbor" not in info
      assert "distance_to_nearest_neighbor" not in info
      assert info["statistics"] == {}
      # Check clustering info
      clustering_info = info["clustering"]
      assert clustering_info["algorithm"] is None
      assert clustering_info["params"] == {}
      assert (
          clustering_info["stats"]["underperforming_cluster_id"]
          == UNDERPERFORMING_CLUSTER_ID
      )
      cluster_labels = clustering_info["stats"]["cluster_ids"]
      issues = issue_manager.issues
      issue_indices = issues.index[
          issues["is_underperforming_group_issue"]
      ].values
      assert np.all(
          cluster_labels[issue_indices] == UNDERPERFORMING_CLUSTER_ID
      ), "All samples with issue should belong to underperforming cluster"
  
      np.testing.assert_equal(
          clustering_info["stats"]["cluster_ids"], labels
      )
  
file_path: cleanlab/tests/datalab/issue_manager/test_underperforming_group.py
imports: import numpy
  import pytest
  import pandas
  import scipy.sparse
  from cleanlab.datalab.internal.issue_manager.underperforming_group import UnderperformingGroupIssueManager
  from sklearn.datasets import make_blobs, load_iris
label_desc: Use image node_id 7 for calling the TestUnderperformingGroupIssueManager obj's underlying member method code with example usage: obj.test_collect_info(issue_manager, make_data) without return types