code: def test_nn_bad_metric_sparse_data(sparse_nn_data):
      with pytest.raises(ValueError):
          nearest_neighbors(
              sparse_nn_data,
              10,
              "seuclidean",
              {},
              False,
              np.random,
          )
  
file_path: umap/umap/tests/test_umap_nn.py
imports: import numpy
  import pytest
  from numpy.testing import assert_array_almost_equal
  from sklearn.neighbors import KDTree
  from sklearn.preprocessing import normalize
  from umap import distances
  from umap.umap_ import nearest_neighbors, smooth_knn_dist
label_desc: Use image node_id 2 for calling a global function with example usage: test_nn_bad_metric_sparse_data(sparse_nn_data) without return types