code: def test_constant_q(
      sr, fmin, n_bins, bins_per_octave, filter_scale, pad_fft, norm
  ):
      with pytest.warns(FutureWarning, match="Deprecated"):
          F, lengths = librosa.filters.constant_q(
              sr=sr,
              fmin=fmin,
              n_bins=n_bins,
              bins_per_octave=bins_per_octave,
              filter_scale=filter_scale,
              pad_fft=pad_fft,
              norm=norm,
          )
  
      assert np.all(lengths <= F.shape[1])
  
      assert len(F) == n_bins
  
      if not pad_fft:
          return
  
      assert np.mod(np.log2(F.shape[1]), 1.0) == 0.0
  
      # Check for vanishing negative frequencies
      F_fft = np.abs(np.fft.fft(F, axis=1))
      # Normalize by row-wise peak
      F_fft = F_fft / np.max(F_fft, axis=1, keepdims=True)
      assert not np.any(F_fft[:, -F_fft.shape[1] // 2 :] > 1e-4)
  
imports: import os
  from contextlib import nullcontext
  import warnings
  import glob
  import numpy
  import scipy.io
  import scipy.signal
  from typing import Any, ContextManager
  import pytest
  import librosa
label_desc: Use image node_id 14 for calling a global function with example usage: test_constant_q(sr, fmin, n_bins, bins_per_octave, filter_scale, pad_fft, norm) without return types