code: def met_stft(y, n_fft, hop_length, win_length, normalize):
      S = np.abs(
          librosa.stft(
              y,
              n_fft=n_fft,
              hop_length=hop_length,
              win_length=win_length,
              window=scipy.signal.windows.hamming,
              center=False,
          )
      )
  
      if normalize:
          S = S / (S[0] + np.sum(2 * S[1:], axis=0))
  
      return S
  
file_path: librosa/tests/test_met_features.py
imports: import os
  import pytest
  import numpy
  import scipy.io
  import scipy.signal
  from test_core import load, files
  import librosa
label_desc: Use image node_id 1 for calling a global function with example usage: met_stft(y, n_fft, hop_length, win_length, normalize) and returns: S