code: def test_spectral_clustering_np_matrix_raises():
      """Check that spectral_clustering raises an informative error when passed
      a np.matrix. See #10993"""
      X = np.matrix([[0.0, 2.0], [2.0, 0.0]])
  
      msg = r"np\.matrix is not supported. Please convert to a numpy array"
      with pytest.raises(TypeError, match=msg):
          spectral_clustering(X)
  
imports: import pickle
  import re
  import numpy
  import pytest
  from scipy.linalg import LinAlgError
  from sklearn.cluster import SpectralClustering, spectral_clustering
  from sklearn.cluster._spectral import cluster_qr, discretize
  from sklearn.datasets import make_blobs
  from sklearn.feature_extraction import img_to_graph
  from sklearn.metrics import adjusted_rand_score
  from sklearn.metrics.pairwise import kernel_metrics, rbf_kernel
  from sklearn.neighbors import NearestNeighbors
  from sklearn.utils import check_random_state
  from sklearn.utils._testing import assert_array_equal
  from sklearn.utils.fixes import COO_CONTAINERS, CSR_CONTAINERS
label_desc: Use image node_id 11 for calling a global function with example usage: test_spectral_clustering_np_matrix_raises() without return types