code: def test_umap_inverse_transform_on_iris(iris, iris_model):
      highd_tree = KDTree(iris.data)
      fitter = iris_model
      lowd_tree = KDTree(fitter.embedding_)
      for i in range(1, 150, 20):
          query_point = fitter.embedding_[i]
          near_points = lowd_tree.query(
              [query_point], k=5, return_distance=False
          )
          centroid = np.mean(
              np.squeeze(fitter.embedding_[near_points]), axis=0
          )
          highd_centroid = fitter.inverse_transform([centroid])
          highd_near_points = highd_tree.query(
              highd_centroid, k=10, return_distance=False
          )
          assert (
              np.intersect1d(near_points, highd_near_points[0]).shape[0]
              >= 3
          )
  
imports: from umap import UMAP
  from umap.umap_ import nearest_neighbors
  from scipy import sparse
  import numpy
  from sklearn.cluster import KMeans
  from sklearn.metrics import adjusted_rand_score
  from sklearn.neighbors import KDTree
  from scipy.spatial.distance import cdist, pdist, squareform
  import pytest
  import warnings
label_desc: Use image node_id 11 for calling a global function with example usage: test_umap_inverse_transform_on_iris(iris, iris_model) without return types