code: def test_real_hpss(S22050, window, power, mask, margin):
      H, P = librosa.decompose.hpss(
          S22050,
          kernel_size=window,
          power=power,
          mask=mask,
          margin=margin,
      )
  
      if margin == 1.0 or margin == (1.0, 1.0):
          if mask:
              assert np.allclose(H + P, np.ones_like(S22050))
          else:
              assert np.allclose(H + P, S22050)
      else:
          if mask:
              assert np.all(H + P <= np.ones_like(S22050))
          else:
              assert np.all(H + P <= S22050)
  
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 11 for calling a global function with example usage: test_real_hpss(S22050, window, power, mask, margin) without return types