code: def test_hdbscan_error_precomputed_and_store_centers(store_centers):
      """Check that we raise an error if the centers are requested together with
      a precomputed input matrix.
  
      Non-regression test for:
      https://github.com/scikit-learn/scikit-learn/issues/27893
      """
      rng = np.random.RandomState(0)
      X = rng.random((100, 2))
      X_dist = euclidean_distances(X)
      err_msg = "Cannot store centers when using a precomputed distance matrix."
      with pytest.raises(ValueError, match=err_msg):
          HDBSCAN(
              metric="precomputed", store_centers=store_centers
          ).fit(X_dist)
  
imports: import numpy
  import pytest
  from scipy import stats
  from scipy.spatial import distance
  from sklearn.cluster import HDBSCAN
  from sklearn.cluster._hdbscan._tree import CONDENSED_dtype, _condense_tree, _do_labelling
  from sklearn.cluster._hdbscan.hdbscan import _OUTLIER_ENCODING
  from sklearn.datasets import make_blobs
  from sklearn.metrics import fowlkes_mallows_score
  from sklearn.metrics.pairwise import _VALID_METRICS, euclidean_distances
  from sklearn.neighbors import BallTree, KDTree
  from sklearn.preprocessing import StandardScaler
  from sklearn.utils import shuffle
  from sklearn.utils._testing import assert_allclose, assert_array_equal
  from sklearn.utils.fixes import CSC_CONTAINERS, CSR_CONTAINERS
label_desc: Use image node_id 27 for calling a global function with example usage: test_hdbscan_error_precomputed_and_store_centers(store_centers) without return types