code: def test_path_enhance(
      R_input,
      window,
      n,
      max_ratio,
      min_ratio,
      n_filters,
      zero_mean,
      clip,
      kwargs,
  ):
      R_smooth = librosa.segment.path_enhance(
          R_input,
          window=window,
          n=n,
          max_ratio=max_ratio,
          min_ratio=min_ratio,
          n_filters=n_filters,
          zero_mean=zero_mean,
          clip=clip,
          **kwargs,
      )
  
      assert R_smooth.shape == R_input.shape
      assert np.all(np.isfinite(R_smooth))
      assert R_smooth.dtype == R_input.dtype
  
      if clip:
          assert np.min(R_smooth) >= 0
  
imports: from typing import Union
  import warnings
  import os
  import numpy
  import scipy
  from scipy.spatial.distance import cdist, pdist, squareform
  import pytest
  from test_core import srand
  import librosa
label_desc: Use image node_id 40 for calling a global function with example usage: test_path_enhance(R_input, window, n, max_ratio, min_ratio, n_filters, zero_mean, clip, kwargs) without return types