code: def test_umap_bad_too_large_min_dist(nn_data):
      u = UMAP(min_dist=2.0)
      # a RuntimeWarning about division by zero in a,b curve fitting is expected
      # caught and ignored for this test
      with warnings.catch_warnings():
          warnings.filterwarnings("ignore", category=RuntimeWarning)
          with pytest.raises(ValueError):
              u.fit(nn_data)
  
imports: import warnings
  import numpy
  from sklearn.metrics import pairwise_distances
  import pytest
  import numba
  from umap import UMAP
  import umap.validation
label_desc: Use image node_id 3 for calling a global function with example usage: test_umap_bad_too_large_min_dist(nn_data) without return types