code: def test_umap_sparse_trustworthiness(sparse_test_data):
      embedding = UMAP(n_neighbors=10, n_epochs=100).fit_transform(
          sparse_test_data[:100]
      )
      trust = trustworthiness(
          sparse_test_data[:100].toarray(), embedding, n_neighbors=10
      )
      assert (
          trust >= 0.88
      ), "Insufficiently trustworthy embedding for sparse test 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 1 for calling a global function with example usage: test_umap_sparse_trustworthiness(sparse_test_data) without return types