code: def test_nn_filter_badselfsim(data, x, y, sparse):
      srand()
      # Build a recurrence matrix, just for testing purposes
      rec = np.random.randn(x, y)
      if sparse:
          rec = scipy.sparse.csr_matrix(rec)
  
      librosa.decompose.nn_filter(data, rec=rec)
  
imports: import os
  import numpy
  import scipy.sparse
  import librosa
  import sklearn.decomposition
  import pytest
  from test_core import srand
label_desc: Use image node_id 20 for calling a global function with example usage: test_nn_filter_badselfsim(data, x, y, sparse) without return types