docstr: Verify the mutual consistency of k-NN distances:
  For every point i and its neighbor j, ensure that the distance from i to j
  cannot be smaller than the distance from any other neighbor k of j to j.
code: def assert_mutual_consistency_of_knn_distances(distances, indices):
      """Verify the mutual consistency of k-NN distances:
      For every point i and its neighbor j, ensure that the distance from i to j
      cannot be smaller than the distance from any other neighbor k of j to j.
      """
      for i in range(distances.shape[0]):
          for j in indices[i]:
              d_ij = distances[i][list(indices[i]).index(j)]
              j_neighbors_distances = distances[j]
              if d_ij < max(j_neighbors_distances):
                  assert (
                      i in indices[j]
                  ), f"Point {i} should be a neighbor of point {j}, it's closer than the farthest neighbor of {j}"
  
file_path: cleanlab/tests/datalab/issue_manager/test_knn_graph.py
imports: import math
  from hypothesis import HealthCheck, given, settings, strategies
  import pytest
  from .conftest import knn_graph_strategy
label_desc: Use image node_id 4 for calling the TestKNNGraph obj's underlying member method code with example usage: obj.assert_mutual_consistency_of_knn_distances(distances, indices) without return types