code: def test_initialize_nn_output():
      # Test that initialization does not return negative values
      rng = np.random.mtrand.RandomState(42)
      data = np.abs(rng.randn(10, 10))
      for init in ("random", "nndsvd", "nndsvda", "nndsvdar"):
          W, H = nmf._initialize_nmf(
              data, 10, init=init, random_state=0
          )
          assert not ((W < 0).any() or (H < 0).any())
  
imports: import re
  import sys
  import warnings
  from io import StringIO
  import numpy
  import pytest
  from scipy import linalg
  from sklearn.base import clone
  from sklearn.decomposition import NMF, MiniBatchNMF, non_negative_factorization
  from sklearn.decomposition import _nmf
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.utils._testing import assert_allclose, assert_almost_equal, assert_array_almost_equal, assert_array_equal, ignore_warnings
  from sklearn.utils.extmath import squared_norm
  from sklearn.utils.fixes import CSC_CONTAINERS, CSR_CONTAINERS
label_desc: Use image node_id 2 for calling a global function with example usage: test_initialize_nn_output() without return types