code: def test_umap_trustworthiness_random_init(nn_data):
      data = nn_data[:50]
      embedding = UMAP(
          n_neighbors=10,
          min_dist=0.01,
          random_state=42,
          n_epochs=100,
          init="random",
      ).fit_transform(data)
      trust = trustworthiness(data, embedding, n_neighbors=10)
      assert trust >= 0.8, (
          "Insufficiently trustworthy embedding for"
          "nn dataset: {}".format(trust)
      )
  
file_path: umap/umap/tests/test_umap_trustworthiness.py
imports: from umap import UMAP
  from sklearn.datasets import make_blobs
  from sklearn.metrics import pairwise_distances
  import numpy
  import scipy.sparse
label_desc: Use image node_id 3 for calling a global function with example usage: test_umap_trustworthiness_random_init(nn_data) without return types