code: def test_connectivity_fixing_non_lil():
      # Check non regression of a bug if a non item assignable connectivity is
      # provided with more than one component.
      # create dummy data
      x = np.array([[0, 0], [1, 1]])
      # create a mask with several components to force connectivity fixing
      m = np.array([[True, False], [False, True]])
      c = grid_to_graph(n_x=2, n_y=2, mask=m)
      w = AgglomerativeClustering(connectivity=c, linkage="ward")
      with pytest.warns(UserWarning):
          w.fit(x)
  
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 19 for calling a global function with example usage: test_connectivity_fixing_non_lil() without return types