code: def test_semisupervised_umap_trustworthiness():
      data, labels = make_blobs(50, cluster_std=0.5, random_state=42)
      labels[10:30] = -1
      embedding = UMAP(
          n_neighbors=10, min_dist=0.01, random_state=42, n_epochs=100
      ).fit_transform(data, labels)
      trust = trustworthiness(data, embedding, n_neighbors=10)
      assert trust >= 0.95, (
          "Insufficiently trustworthy embedding for"
          "blobs 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 5 for calling a global function with example usage: test_semisupervised_umap_trustworthiness() without return types