code: def test_local_clustering(aligned_iris, aligned_iris_model):
      data, target = aligned_iris
  
      embd = aligned_iris_model.embeddings_[1]
      clusters = KMeans(n_clusters=2).fit_predict(embd)
      ari = adjusted_rand_score(target[1], clusters)
      assert ari >= 0.75
  
      embd = aligned_iris_model.embeddings_[3]
      clusters = KMeans(n_clusters=2).fit_predict(embd)
      ari = adjusted_rand_score(target[3], clusters)
      assert ari >= 0.40
  
file_path: umap/umap/tests/test_aligned_umap.py
imports: import pytest
  from umap import AlignedUMAP
  from sklearn.metrics import pairwise_distances
  from sklearn.cluster import KMeans
  import numpy
  from sklearn.metrics import adjusted_rand_score
label_desc: Use image node_id 3 for calling a global function with example usage: test_local_clustering(aligned_iris, aligned_iris_model) without return types