code: def test_small_distance_threshold(global_random_seed):
      rng = np.random.RandomState(global_random_seed)
      n_samples = 10
      X = rng.randint(-300, 300, size=(n_samples, 3))
      # this should result in all data in their own clusters, given that
      # their pairwise distances are bigger than .1 (which may not be the case
      # with a different random seed).
      clustering = AgglomerativeClustering(
          n_clusters=None, distance_threshold=1.0, linkage="single"
      ).fit(X)
      # check that the pairwise distances are indeed all larger than .1
      all_distances = pairwise_distances(X, metric="minkowski", p=2)
      np.fill_diagonal(all_distances, np.inf)
      assert np.all(all_distances > 0.1)
      assert clustering.n_clusters_ == n_samples
  
imports: import itertools
  import shutil
  from functools import partial
  from tempfile import mkdtemp
  import numpy
  import pytest
  from scipy.cluster import hierarchy
  from scipy.sparse.csgraph import connected_components
  from sklearn.cluster import AgglomerativeClustering, FeatureAgglomeration, ward_tree
  from sklearn.cluster._agglomerative import _TREE_BUILDERS, _fix_connectivity, _hc_cut, linkage_tree
  from sklearn.cluster._hierarchical_fast import average_merge, max_merge, mst_linkage_core
  from sklearn.datasets import make_circles, make_moons
  from sklearn.feature_extraction.image import grid_to_graph
  from sklearn.metrics import DistanceMetric
  from sklearn.metrics.cluster import adjusted_rand_score, normalized_mutual_info_score
  from sklearn.metrics.pairwise import PAIRED_DISTANCES, cosine_distances, manhattan_distances, pairwise_distances
  from sklearn.metrics.tests.test_dist_metrics import METRICS_DEFAULT_PARAMS
  from sklearn.neighbors import kneighbors_graph
  from sklearn.utils._fast_dict import IntFloatDict
  from sklearn.utils._testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal, create_memmap_backed_data, ignore_warnings
  from sklearn.utils.fixes import LIL_CONTAINERS
label_desc: Use image node_id 27 for calling a global function with example usage: test_small_distance_threshold(global_random_seed) without return types